Building data platform with an enrichment loop

ABSTRACT

A building system including one or more memory devices having instructions stored thereon, that, when executed by one or more processors, cause the one or more processors to receive an event from an event source, the event comprising data and a timestamp. The building system operates to identify first contextual data describing the event in a digital twin, the digital twin comprising a virtual representation of a building, enrich the event with the first contextual data, and provide the enriched event to a consuming system, the consuming system generating an output event based on the enriched event. The building system operates to identify second contextual data describing the output event in the digital twin, enrich the output event with the second contextual data, and provide the enriched output event to the consuming system or another consuming system.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application claims the benefit of and priority to U.S. ProvisionalPatent Application No. 63/347,485 filed May 31, 2022 and is acontinuation-in-part of U.S. patent application Ser. No. 17/678,260filed Feb. 23, 2022, which is a continuation of U.S. patent applicationSer. No. 17/504,121 filed Oct. 18, 2021, which is a continuation of U.S.patent application Ser. No. 17/134,659 filed Dec. 28, 2020 (now U.S.Pat. No. 11,150,617) which claims the benefit of and priority to U.S.Provisional Patent Application No. 62/955,856 filed Dec. 31st , 2019,U.S. Provisional Patent Application No. 63/005,841 filed Apr. 6th ,2020, and U.S. Provisional Patent Application No. 63/105,754 filed Oct.26, 2020. The entirety of each these patent applications is incorporatedby reference herein.

BACKGROUND

The present disclosure relates generally to the management of buildingsystems of a building. The present disclosure relates more particularlyto the control of building systems through a cloud based system. Abuilding can include various types of building subsystems, e.g.,heating, ventilation, and air conditioning (HVAC) systems, securitysystems, fire response systems, etc. Discrete predefined controllingsystems may operate each subsystem individually without knowledge of thebuilding. However, discrete predefined controlling systems may not allowfor dynamic, scalable, and adjustable solutions that can provideholistic management of a building.

SUMMARY Enrichment Loop

One implementation of the present disclosure is a building systemincluding one or more memory devices having instructions thereon, that,when executed by one or more processors, cause the one or moreprocessors to receive an event from an event source, the eventcomprising data and a timestamp. The instructions cause the one or moreprocessors to identify first contextual data describing the event in adigital twin, the digital twin comprising a virtual representation of abuilding. The instructions cause the one or more processors to enrichthe event with the first contextual data. The instructions cause the oneor more processors to provide the enriched event to a consuming system,the consuming system generating an output event based on the enrichedevent. The instructions cause the one or more processors to identifysecond contextual data describing the output event in the digital twin.The instructions cause the one or more processors to enrich the outputevent with the second contextual data. The instructions cause the one ormore processors to provide the enriched output event to the consumingsystem or another consuming system.

In some embodiments, the instructions cause the one or more processorsto execute an enrichment pipeline, the enrichment pipeline identifyingthe first contextual data, enriching the event with the first contextualdata, and outputting the enriched event and feed the output event backinto an input of the enrichment pipeline, the enrichment pipelineidentifying the second contextual data, enriching the output event withthe second contextual data, and outputting the enriched output event.

In some embodiments, the consuming system generates the output eventbased on the data of the enriched event and the first contextual data ofthe enriched event.

In some embodiments, the instructions cause the one or more processorsto execute one or more enrichment rules to identify the contextual datafrom the digital twin, the digital twin comprising a plurality of typesof contextual data for a plurality of event sources, and the one or moreenrichment rules identifying types of contextual information for theevent source.

In some embodiments, the instructions cause the one or more processorsto identify the first contextual data by performing a first search ofthe digital twin and identify the second contextual data by performing asecond search of the digital twin.

In some embodiments, the digital twin includes a building graph and theinstructions cause the one or more processors to identify the firstcontextual data by performing a first search of the building graph andidentify the second contextual data by performing a second search of thebuilding graph.

In some embodiments, the contextual data includes at least one of alocation within the building that the event source is located, anindication of one or more pieces of building equipment of the eventsource, or one or more capabilities associated with the pieces ofbuilding equipment.

In some embodiments, the event source is at least one of an internaldata source located within the building or an external data sourcelocated outside the building.

In some embodiments, the digital twin includes a building graph, thebuilding graph including a plurality of nodes representing a pluralityof entities of the building. In some embodiments, at least a portion ofthe plurality of nodes represent the first contextual data, the secondcontextual data, the event source, and the consuming system and aplurality of edges between the plurality of nodes. In some embodiments,the plurality of edges represent relationships between the plurality ofentities of the building.

In some embodiments, the instructions cause the one or more processorsto identify the first contextual data by identifying a first node of theplurality of nodes representing the event source and identifying a firstedge of the plurality of edges between the first node and a second noderepresenting the first contextual data.

In some embodiments, the instructions cause the one or more processorsto execute a first machine learning model using the enriched event togenerate an inference of a characteristic of the building, identify asecond machine learning model that executes on the inference of thecharacteristic of the building, and communicate the inference of thecharacteristic to the second machine learning model.

In some embodiments, the instructions cause the one or more processorsto identify third contextual data of the digital twin for the inferenceof the characteristic of the building, enrich the inference with thethird contextual data, and execute the second machine learning modelbased on the inference enriched with the third contextual data.

In some embodiments, the instructions cause the one or more processorsto generate a subscription that routes the inference to the secondmachine learning model responsive to identifying that the second machinelearning model executes on the inference of the characteristic of thebuilding and provide the inference, based on the subscription, to thesecond machine learning model.

Another implementation of the present disclosure is a method includingreceiving, by a processing circuit, from an event source, an event, theevent comprises data and a timestamp. The method further includesidentifying, by the processing circuit, first contextual data describingthe event in a digital twin, the digital twin comprising a virtualrepresentation of a building. The method further includes enriching, bythe processing circuit, the event with the first contextual data. Themethod further includes providing, by the processing circuit, to aconsuming system, the enriched event, the consuming system generating anoutput event based on the enriched event. The method further includesidentifying, by the processing circuit, second contextual datadescribing the output event in the digital twin. The method furtherincludes enriching, by the processing circuit, the output event with thesecond contextual data and providing, by the processing circuit, to theconsuming system or another consuming system, the enriched output event.

In some embodiments, the method includes executing, by the processingcircuit, an enrichment pipeline, the enrichment pipeline identifying thefirst contextual data, enriching the event with the first contextualdata, and outputting the enriched event and feeding, by the processingcircuit, the output event back into an input of the enrichment pipeline,the enrichment pipeline identifying the second contextual data,enriching the output event with the second contextual data, andoutputting the enriched output event.

In some embodiments, the method includes executing, by the processingcircuit, a first machine learning model using the enriched event togenerate an inference of a characteristic of the building, identifying,by the processing circuit, a second machine learning model that executeson the inference of the characteristic of the building, andcommunicating, by the processing circuit, the inference of thecharacteristic to the second machine learning model.

In some embodiments, the method includes identifying, by the processingcircuit, third contextual data of the digital twin for the inference ofthe characteristic of the building, enriching, by the processingcircuit, the inference with the third contextual data, and executing, bythe processing circuit, the second machine learning model based on theinference enriched with the third contextual data.

In some embodiments, the method includes executing, by the processingcircuit, one or more enrichment rules to identify the contextual datafrom the digital twin, the digital twin comprising a plurality of typesof contextual data for a plurality of event sources and the one or moreenrichment rules identifying types of contextual information for theevent source.

In some embodiments, the digital twin includes a building graph. In someembodiments, the building graph includes a plurality of nodesrepresenting a plurality of entities of the building, where at least aportion of the plurality of nodes represent the first contextual data,the second contextual data, the event source, and the consuming system.In some embodiments, the building graph includes a plurality of edgesbetween the plurality of nodes, where the plurality of edges representrelationships between the plurality of entities of the building.

Another implementation of the present disclosure is a building systemincluding one or more memory devices having instructions thereon and oneor more processors configured to execute the instructions causing theone or more processors to receive an event from an event source, theevent comprising data and a timestamp, identify first contextual datadescribing the event in a digital twin, the digital twin comprising avirtual representation of a building, enrich the event with the firstcontextual data, provide the enriched event to a consuming system, theconsuming system generating an output event based on the enriched event,identify second contextual data describing the output event in thedigital twin, enrich the output event with the second contextual data,and provide the enriched output event to the consuming system or anotherconsuming system.

Event Subscriptions

One implementation of the present disclosure is a building systemincluding one or more memory devices having instructions thereon, that,when executed by one or more processors, cause the one or moreprocessors to generate an event subscription for a consuming system, theevent subscription defining events to be sent to the consuming system,receive an event from an event source, the event comprising data and atimestamp, identify contextual data describing the event in a digitaltwin, the digital twin comprising a virtual representation of abuilding, enrich the event with the contextual data, and provide, basedon the event subscription and the contextual data of the enriched event,the enriched event to the consuming system.

In some embodiments, the instructions cause the one or more processorsto receive a second event from a second event source, the second eventsource replacing the event source, identify second contextual datadescribing the second event, the second contextual data including atleast a portion of the first contextual data, enrich the second eventwith the second contextual data, and provide, based on the eventsubscription and the portion of the contextual data of the secondcontextual data, the enriched second event to the consuming system.

In some embodiments, the instructions cause the one or more processorsto receive a request from a second consuming system, where the requestincludes one or more parameters defining events to be sent to the secondconsuming system, identify the event subscription based on the one ormore parameters, and enroll the second consuming system in the eventsubscription responsive to identifying the event subscription.

In some embodiments, the contextual data defines one or more types ofpieces of building equipment and one or more locations of the building.

In some embodiments, the instructions cause the one or more processorsto execute one or more enrichment rules to identify the contextual datafrom the digital twin, the digital twin comprising a plurality of typesof contextual data for a plurality of event sources and the one or moreenrichment rules identifying types of contextual information for theevent source.

In some embodiments, the instructions cause the one or more processorsto identify the first contextual data by performing a first search ofthe digital twin and identify the second contextual data by performing asecond search of the digital twin.

In some embodiments, the digital twin includes a building graph. In someembodiments, the instructions cause the one or more processors toidentify the first contextual data by performing a first search of thebuilding graph and identify the second contextual data by performing asecond search of the building graph.

In some embodiments, the contextual data includes at least one of alocation within the building that the event source is located, anindication of one or more pieces of building equipment of the eventsource, or one or more capabilities associated with the pieces ofbuilding equipment.

In some embodiments, the event source is at least one of an internaldata source located within the building or an external data sourcelocated outside the building.

In some embodiments, the digital twin includes a building graph. In someembodiments, the building graph includes a plurality of nodesrepresenting a plurality of entities of the building, where at least aportion of the plurality of nodes represent the first contextual data,the second contextual data, the event source, and the consuming system,and a plurality of edges between the plurality of nodes, wherein theplurality of edges represent relationships between the plurality ofentities of the building.

In some embodiments, the instructions cause the one or more processorsto identify a first node of the plurality of nodes representing theevent source, determine whether the events associated with the eventsource impacts an entity of the plurality of entities represented by asecond node of the plurality of nodes, generate, responsive todetermining that the events associated with the first node impact thesecond node, identify a consuming system associated with the secondnode, and generate an event subscription for the consuming system, theevent subscription routing enriched events of the event source to theconsuming systems.

Another implementation of the present disclosure is a method includinggenerating, by a processing circuit, an event subscription for aconsuming system, the event subscription defining events to be sent tothe consuming system, receiving, by the processing circuit, an eventfrom an event source, the event comprising data and a timestamp,identifying, by the processing circuit, contextual data describing theevent in a digital twin, the digital twin comprising a virtualrepresentation of a building, enriching, by the processing circuit, theevent with the contextual data, and providing, by the processingcircuit, based on the event subscription and the contextual data of theenriched event, the enriched event to the consuming system.

In some embodiments, the method includes receiving, by the processingcircuit, a second event from a second event source, the second eventsource replacing the event source, identifying, by the processingcircuit, second contextual data describing the second event, the secondcontextual data including at least a portion of the first contextualdata, enriching, by the processing circuit, the second event with thesecond contextual data, and providing, by the processing circuit, basedon the event subscription and the portion of the contextual data of thesecond contextual data, the enriched second event to the consumingsystem.

In some embodiments, the method includes receiving, by the processingcircuit, a request from a second consuming system, wherein the requestincludes one or more parameters defining events to be sent to the secondconsuming system, identifying, by the processing circuit, the eventsubscription based on the one or more parameters, and enrolling, by theprocessing circuit, the second consuming system in the eventsubscription responsive to identifying the event subscription.

In some embodiments, the method includes identifying, by the processingcircuit, the first contextual data by performing a first search of thedigital twin, and identifying, by the processing circuit, the secondcontextual data by performing a second search of the digital twin.

In some embodiments, the digital twin includes a building graph. In someembodiments, the method includes identifying, by the processing circuit,the first contextual data by performing a first search of the buildinggraph, and identifying, by the processing circuit, the second contextualdata by performing a second search of the building graph.

In some embodiments, the contextual data includes at least one of alocation within the building that the event source is located, anindication of one or more pieces of building equipment of the eventsource, or one or more capabilities associated with the pieces ofbuilding equipment.

In some embodiments, the digital twin includes a building graph. In someembodiments, the building graph includes a plurality of nodesrepresenting a plurality of entities of the building, wherein at least aportion of the plurality of nodes represent the first contextual data,the second contextual data, the event source, and the consuming system,and a plurality of edges between the plurality of nodes, wherein theplurality of edges represent relationships between the plurality ofentities of the building.

In some embodiments, the method includes identifying, by the processingcircuit, a first node of the plurality of nodes representing the eventsource, determining, by the processing circuit, whether the eventsassociated with the event source impacts an entity of the plurality ofentities represented by a second node of the plurality of nodes,generating, by the processing circuit, responsive to determining thatthe events associated with the first node impact the second node,identifying, by the processing circuit, a consuming system associatedwith the second node, and generating, by the processing circuit, anevent subscription for the consuming system, the event subscriptionrouting enriched events of the event source to the consuming systems.

Another implementation of the present disclosure is a building systemincluding one or more memory devices having instructions thereon and oneor more processors configured to execute the instructions causing theone or more processors to generate an event subscription for a consumingsystem, the event subscription defining events to be sent to theconsuming system, receive an event from an event source, the eventcomprising data and a timestamp, identify contextual data describing theevent in a digital twin, the digital twin comprising a virtualrepresentation of a building, enrich the event with the contextual data,and provide, based on the event subscription and the contextual data ofthe enriched event, the enriched event to the consuming system.

BRIEF DESCRIPTION OF THE DRAWINGS

Various objects, aspects, features, and advantages of the disclosurewill become more apparent and better understood by referring to thedetailed description taken in conjunction with the accompanyingdrawings, in which like reference characters identify correspondingelements throughout. In the drawings, like reference numbers generallyindicate identical, functionally similar, and/or structurally similarelements.

FIG. 1 is a block diagram of a building data platform including an edgeplatform, a cloud platform, and a twin manager, according to anexemplary embodiment.

FIG. 2 is a block diagram of the cloud platform and the twin manager ofFIG. 1 processing an event received from the edge platform of FIG. 1,according to an exemplary embodiment.

FIG. 3 is a block diagram of the cloud platform of FIG. 1 processingevents shown in greater detail, according to an exemplary embodiment.

FIG. 4 is a block diagram of the twin manager of FIG. 1 generatingprojections and operating with components of the cloud platform of FIG.1 to enrich events, according to an exemplary embodiment.

FIG. 5 is a flow diagram of a preprocessing workflow performed by thecloud platform of FIG. 1 to preprocess events, according to an exemplaryembodiment.

FIG. 6 is a flow diagram of a discovery workflow discovering newentities from metadata and a device tree that is performed by the cloudplatform of FIG. 1, according to an exemplary embodiment.

FIG. 7 is a flow diagram of a projection workflow performed by the twinmanager of FIG. 1 generating a projection, according to an exemplaryembodiment.

FIG. 8 is a flow diagram of an enrichment workflow performed by thecloud platform of FIG. 1 enriching events with contextual information,according to an exemplary embodiment.

FIG. 9 is a flow diagram of a command processing workflow performed bythe cloud platform of FIG. 1 where commands are sent to devices or arecommunicated to an external system via a connection broker, according toan exemplary embodiment.

FIG. 10 is a flow diagram of a messaging workflow performed by the cloudplatform of FIG. 1 where messages of building systems are received viathe edge platform of FIG. 1 and commands for the building systems arecommunicated to the building subsystems via the edge platform, accordingto an exemplary embodiment.

FIG. 11 is a graph projection of the twin manager of FIG. 1 includingapplication programming interface (API) data, capability data, policydata, and services, according to an exemplary embodiment.

FIG. 12 is another graph projection of the twin manager of FIG. 1including application programming interface (API) data, capability data,policy data, and services, according to an exemplary embodiment.

FIG. 13 is a graph projection of the twin manager of FIG. 1 includingequipment and capability data for the equipment, according to anexemplary embodiment.

FIG. 14 is a block diagram of a user interaction manager that handlesuser queries and requests, according to an exemplary embodiment.

FIG. 15 is a flow diagram of a process of a security dashboardcommunicating with the building data platform of FIG. 1 to reviewinformation about equipment and command the equipment, according to anexemplary embodiment.

FIG. 16 is a flow diagram of a process where an event of buildingequipment is enriched with contextual information of a graph that can beperformed by the cloud platform of FIG. 1, according to an exemplaryembodiment.

FIG. 17 is a flow diagram of a process where a change feed of eventsthat record modifications to a graph that can be performed by the twinmanager of FIG. 1, according to an exemplary embodiment.

FIG. 18 is a flow diagram of a process where a graph identifyingcapabilities of a piece of equipment is used to operate the piece ofequipment that can be performed by the cloud platform of FIG. 1,according to an exemplary embodiment.

FIG. 19 is a flow diagram of a process where the cloud platform of FIG.1 operates different services related by a graph, according to anexemplary embodiment.

FIG. 20 is a flow diagram of a process where a user or service isprovided with information and control abilities based on policies storedwithin a graph that can be performed by the cloud platform of FIG. 1,according to an exemplary embodiment.

FIG. 21 is a flow diagram of a process where a graph projection isconstructed for a system based on projection rules, according to anexemplary embodiment.

FIG. 22 is a flow diagram of a process where a graph is queried based onentity and event, according to an exemplary embodiment.

FIG. 23 is a block diagram of a platform manager of the cloud platformof FIG. 1 managing tenant and subscription entitlements with a tenantentitlement model, according to an exemplary embodiment.

FIG. 24 is a block diagram of the tenant entitlement model in greaterdetail, according to an exemplary embodiment.

FIG. 25 is a flow diagram of a process of managing tenant andsubscription entitlements with the tenant entitlement model, accordingto an exemplary embodiment.

FIG. 26 is a block diagram of the edge platform of FIG. 1 performingevent enrichment at the edge before the events are communicated to thecloud, according to an exemplary embodiment.

FIG. 27 is a flow diagram of a process of performing event enrichment atthe edge by the edge platform of FIG. 1 before the events arecommunicated to the cloud, according to an exemplary embodiment.

FIG. 28 is a block diagram of the twin manager of FIG. 1 synchronizing adigital twin of the twin manager with digital twins of other externalsystems, according to an exemplary embodiment.

FIG. 29 is a flow diagram of a process of synchronizing a digital twinof the twin manager with digital twins of other external system,according to an exemplary embodiment.

FIG. 30 is a block diagram of an enrichment loop system, according to anexemplary embodiment.

FIG. 31 is a block diagram of an inference system, according to anexemplary embodiment.

FIG. 32 is an impact graph, according to an exemplary embodiment.

FIG. 33 is a flow diagram of a process of enriching events, according toan exemplary embodiment.

FIG. 34 is a flow diagram of a process of generating subscriptions,according to an exemplary embodiment.

DETAILED DESCRIPTION

Referring generally to the FIGURES, a building data platform is shown,according to various exemplary embodiments. The building data platformdescribed herein can be configured to facilitate the management andcontrol of a building. The building data platform can provide agility,flexibility, and scalability for building management, enabling buildingsto be dynamic spaces. The building data platform can allow users to beable to manage operations with buildings that have memory, intelligence,and unique identities. The building data platform can be configured toperform energy and space optimization, predictive maintenance, and/orremote operations. Although the building data platform is described fora building, e.g., for building subsystems of a building (e.g., for HVACsystems, security systems, access control systems, elevator systems,fire response systems, etc.), the building data platform can be appliedto other industries, e.g., motor vehicles, airports, manufacturingsystems, transit systems, airplanes, and/or any other type of systemwhere the management of devices is desired. The building data platformcan provide seamless integration of devices regardless of brand, make,model, or subsystem.

The building data platform can include multiple components, e.g., anedge platform, a cloud platform, and a twin manager. The edge platformcan be configured to facilitate connection for the building dataplatform directly to the building systems. The edge platform canfacilitate receiving, collecting, and/or retrieving data from thebuilding subsystems. In some embodiments, the edge platform canfacilitate the command and control of the building systems for thebuilding data platform.

The cloud platform can be configured to facilitate message control forthe building data platform. The cloud platform can be configured toreceive messages of the building subsystems through the edge platformand manage the messages. The cloud platform can route messages aroundthe building data platform. Furthermore, the cloud platform canfacilitate directing operational commands for the building subsystems tothe building subsystems through the edge platform. In some embodiments,the cloud platform is configured to enrich messages received from thebuilding subsystems. The cloud platform can be configured to addcontextual information to event messages received from the buildingsubsystems via the edge platform. The contextual information can beutilized by applications that consume the event messages and can allowfor the applications to immediately have access to the contextualinformation instead of requiring the applications to query anothersystem to receive contextual information.

The twin manager can facilitate the management of a digital twin of thebuilding, e.g., the building subsystems. Digital twins can be digitalreplicas of physical entities that enable an in-depth analysis of dataof the physical entities and provide the potential to monitor systems tomitigate risks, manage issues, and utilize simulations to test futuresolutions. Digital twins can play an important role in helpingtechnicians find the root cause of issues and solve problems faster, insupporting safety and security protocols, and in supporting buildingmanagers in more efficient use of energy and other facilities resources.Digital twins can be used to enable and unify security systems, employeeexperience, facilities management, sustainability, etc.

The twin manager can be configured to track the building subsystems bystoring entities (e.g., data representing equipment, buildings, spaces,floors, software services, policies, etc.), relationships (e.g.,relationships between equipment and their locations, API calls betweensoftware services, etc.), and events (e.g., data that has occurred,measurements, commands, statuses, etc.). The twin manager can creategraph projections, e.g., a graph with nodes for the entities and eventsof the building and edges for the relationships between the entitiesand/or events. The graph projections can be built on particular policies(e.g., what entities, events, and/or relationships should be includedwithin the graph) and/or ontologies (the types of relationships thatshould be made with different types of entities and/or events). In thisregard, particular graph projections can be generated for particularsubscribers, users, systems, etc.

The edge platform, the cloud platform and/or the twin manager canfacilitate one or more enrichment loops. The enrichment loops can befacilitated by enriching one or more event messages and/or enriching oneor more application messages and then further enriching the enrichedmessages by combining the enriched event messages and/or the enrichedapplication message with contextual data. An event message can beenriched by combining the event message and the contextual data thatpertains to the event message. An application message can be enriched bycombining the application message and the contextual data that pertainsto the application message.

In some embodiments, the cloud platform can receive an event message.The cloud platform can enrich the event message by enriching the eventmessage with contextual information that pertains to the event message.The cloud platform can provide the enriched event message to anapplication. The application can use the event message to generate anapplication message. In some embodiments, the application message can bethe application performing an action. For example, the application canbe an HVAC device and the application message can be a messageindicating that the ventilation rate for the HVAC device has beenadjusted. In some embodiments, the cloud platform can receive theapplication message. The cloud platform can enrich the applicationmessage by combining the application message and the contextualinformation that pertains to the application message.

One technical advantage of enrichment loops can be that the enrichmentloops facilitate continuous updating of messages. The continuousupdating of messages can provide additional flexibility to a buildingsystem. For example, a message that is enriched by combining an eventand the contextual information pertaining to an event enables anapplication to have immediate access to the contextual information.Additionally, the message generated using an enrichment loop providesthe contextual information pertaining to an event while also providingcontextual information that pertains to one or more additional events.The application that receives the message generated using the enrichmentloops has greater flexibility in that the application has immediateaccess to the contextual information of one or more events without theapplication having queried the system to receive the contextualinformation pertaining to the additional events.

The edge platform, the cloud platform and/or the twin manager canfacilitate one or more event subscriptions. The event subscriptions canlink one or more events with one or more applications and/or edgedevices. In some embodiments, an application can enroll in one or moreevent subscriptions by providing a request to enroll in the eventsubscriptions. The request can define one or more events that theapplication would like to receive. The event subscriptions allow greaterflexibility as the application does not need to specify event sourceswhen requesting to enroll in the event subscription. For example, anapplication can request to enroll in an event subscription that providesoccupancy events without providing one or more occupancy event sources.The edge platform, the cloud platform and/or the twin manager canidentify one or more event sources that produce the events included inthe request. The application once enrolled in the event subscription canreceive events that have been linked to the event subscription.

In some embodiments, the cloud platform can receive a request from anapplication to enroll in an event subscription. The cloud platform cancheck an event subscription database to determine whether the eventsubscription has already been generated. In some embodiments, the cloudplatform, upon determining that the event subscription has already beengenerated, can enroll the application in the event subscription. In someembodiments, the cloud platform can determine that the eventsubscription has not been generated and the cloud platform can thengenerate a new event subscription. Additionally, the cloud platform canenroll the application in the new event subscription. Furthermore, thecloud platform can add the new event subscription to the eventsubscription database.

One technical advantage of event subscriptions can be that anapplication can make a single request to receive one or more events andthen as the events occur the application can receive the events. Theevent subscriptions allows the application to receive events without theapplication providing any additional requests. Additionally, the eventsubscriptions are event dependent and not device dependent. For example,a consuming device can enroll in a subscription that can provide eventsthat pertain to temperature measurements. One technical advantage ofevent subscriptions can be that when an event source is replaced (e.g.,the event source no longer works) with a new event source, the consumingdevice does not need to request to enroll in a new event subscription.The original event subscription can include the new event source giventhat the new event source produces the same type of events as eventsource that was replaced (e.g., the new event source also producestemperature measurements). The ability to include a new event source toan event subscriptions allows for an application to continue to receiveevents pertaining to an event subscription without needing to known theevent source or that the event source is new.

Referring now to FIG. 1, a building data platform 100 including an edgeplatform 102, a cloud platform 106, and a twin manager 108 are shown,according to an exemplary embodiment. The edge platform 102, the cloudplatform 106, and the twin manager 108 can each be separate servicesdeployed on the same or different computing systems. In someembodiments, the cloud platform 106 and the twin manager 108 areimplemented in off premises computing systems, e.g., outside a building.The edge platform 102 can be implemented on-premises, e.g., within thebuilding.

The building data platform 100 includes applications 110. Theapplications 110 can be various applications that operate to manage thebuilding subsystems 122. The applications 110 can be remote oron-premises applications that run on various computing systems. Theapplications 110 can include an alarm application 168 configured tomanage alarms for the building subsystems 122. The applications 110include an assurance application 170 that implements assurance servicesfor the building subsystems 122. In some embodiments, the applications110 include an energy application 172 configured to manage the energyusage of the building subsystems 122. The applications 110 include asecurity application 174 configured to manage security systems of thebuilding.

In some embodiments, the applications 110 and/or the cloud platform 106interacts with a user device 176. In some embodiments, a component or anentire application of the applications 110 runs on the user device 176.The user device 176 may be a laptop computer, a desktop computer, asmartphone, a tablet, and/or any other device with an input interface(e.g., touch screen, mouse, keyboard, etc.) and an output interface(e.g., a speaker, a display, etc.).

The applications 110, the twin manager 108, the cloud platform 106, andthe edge platform 102 can be implemented on one or more computingsystems, e.g., on processors and/or memory devices. For example, theedge platform 102 includes processor(s) 118 and memories 120, the cloudplatform 106 includes processor(s) 124 and memories 126, theapplications 110 include processor(s) 164 and memories 166, and the twinmanager 108 includes processor(s) 148 and memories 150.

The processors can be a general purpose or specific purpose processor,an application specific integrated circuit (ASIC), one or more fieldprogrammable gate arrays (FPGAs), a group of processing components, orother suitable processing components. The processors may be configuredto execute computer code and/or instructions stored in the memories orreceived from other computer readable media (e.g., CDROM, networkstorage, a remote server, etc.).

The memories can include one or more devices (e.g., memory units, memorydevices, storage devices, etc.) for storing data and/or computer codefor completing and/or facilitating the various processes described inthe present disclosure. The memories can include random access memory(RAM), read-only memory (ROM), hard drive storage, temporary storage,non-volatile memory, flash memory, optical memory, or any other suitablememory for storing software objects and/or computer instructions. Thememories can include database components, object code components, scriptcomponents, or any other type of information structure for supportingthe various activities and information structures described in thepresent disclosure. The memories can be communicably connected to theprocessors and can include computer code for executing (e.g., by theprocessors) one or more processes described herein.

The edge platform 102 can be configured to provide connection to thebuilding subsystems 122. The edge platform 102 can receive messages fromthe building subsystems 122 and/or deliver messages to the buildingsubsystems 122. The edge platform 102 includes one or multiple gateways,e.g., the gateways 112-116. The gateways 112-116 can act as a gatewaybetween the cloud platform 106 and the building subsystems 122. Thegateways 112-116 can be the gateways described in U.S. ProvisionalPatent Application No. 62/951,897 filed Dec. 20th, 2019, the entirety ofwhich is incorporated by reference herein. In some embodiments, theapplications 110 can be deployed on the edge platform 102. In thisregard, lower latency in management of the building subsystems 122 canbe realized.

The edge platform 102 can be connected to the cloud platform 106 via anetwork 104. The network 104 can communicatively couple the devices andsystems of building data platform 100. In some embodiments, the network104 is at least one of and/or a combination of a Wi-Fi network, a wiredEthernet network, a ZigBee network, a Bluetooth network, and/or anyother wireless network. The network 104 may be a local area network or awide area network (e.g., the Internet, a building WAN, etc.) and may usea variety of communications protocols (e.g., BACnet, IP, LON, etc.). Thenetwork 104 may include routers, modems, servers, cell towers,satellites, and/or network switches. The network 104 may be acombination of wired and wireless networks.

The cloud platform 106 can be configured to facilitate communication androuting of messages between the applications 110, the twin manager 108,the edge platform 102, and/or any other system. The cloud platform 106can include a platform manager 128, a messaging manager 140, a commandprocessor 136, and an enrichment manager 138. In some embodiments, thecloud platform 106 can facilitate messaging between the building dataplatform 100 via the network 104.

The messaging manager 140 can be configured to operate as a transportservice that controls communication with the building subsystems 122and/or any other system, e.g., managing commands to devices (C2D),commands to connectors (C2C) for external systems, commands from thedevice to the cloud (D2C), and/or notifications. The messaging manager140 can receive different types of data from the applications 110, thetwin manager 108, and/or the edge platform 102. The messaging manager140 can receive change on value data 142, e.g., data that indicates thata value of a point has changed. The messaging manager 140 can receivetimeseries data 144, e.g., a time correlated series of data entries eachassociated with a particular time stamp. Furthermore, the messagingmanager 140 can receive command data 146. All of the messages handled bythe cloud platform 106 can be handled as an event, e.g., the data142-146 can each be packaged as an event with a data value occurring ata particular time (e.g., a temperature measurement made at a particulartime).

The cloud platform 106 includes a command processor 136. The commandprocessor 136 can be configured to receive commands to perform an actionfrom the applications 110, the building subsystems 122, the user device176, etc. The command processor 136 can manage the commands, determinewhether the commanding system is authorized to perform the particularcommands, and communicate the commands to the commanded system, e.g.,the building subsystems 122 and/or the applications 110. The commandscould be a command to change an operational setting that controlenvironmental conditions of a building, a command to run analytics, etc.

The cloud platform 106 includes an enrichment manager 138. Theenrichment manager 138 can be configured to enrich the events receivedby the messaging manager 140. The enrichment manager 138 can beconfigured to add contextual information to the events. The enrichmentmanager 138 can communicate with the twin manager 108 to retrieve thecontextual information. In some embodiments, the contextual informationis an indication of information related to the event. For example, ifthe event is a timeseries temperature measurement of a thermostat,contextual information such as the location of the thermostat (e.g.,what room), the equipment controlled by the thermostat (e.g., what VAV),etc. can be added to the event. In this regard, when a consumingapplication, e.g., one of the applications 110 receives the event, theconsuming application can operate based on the data of the event, thetemperature measurement, and also the contextual information of theevent.

The enrichment manager 138 can solve a problem that when a deviceproduces a significant amount of information, the information maycontain simple data without context. An example might include the datagenerated when a user scans a badge at a badge scanner of the buildingsubsystems 122. This physical event can generate an output eventincluding such information as “DeviceBadgeScannerID,” “BadgeID,” and/or“Date/Time.” However, if a system sends this data to a consumingapplication, e.g., Consumer A and a Consumer B, each customer may needto call the building data platform knowledge service to queryinformation with queries such as, “What space, build, floor is thatbadge scanner in?” or “What user is associated with that badge?”

By performing enrichment on the data feed, a system can be able toperform inferences on the data. A result of the enrichment may betransformation of the message “DeviceBadgeScannerId, BadgeId,Date/Time,” to “Region, Building, Floor, Asset, DeviceId, BadgeId,UserName, EmployeeId, Date/Time Scanned.” This can be a significantoptimization, as a system can reduce the number of calls by 1/n, where nis the number of consumers of this data feed.

By using this enrichment, a system can also have the ability to filterout undesired events. If there are 100 building in a campus that receive100,000 events per building each hour, but only 1 building is actuallycommissioned, only 1/10 of the events are enriched. By looking at whatevents are enriched and what events are not enriched, a system can dotraffic shaping of forwarding of these events to reduce the cost offorwarding events that no consuming application wants or reads.

An example of an event received by the enrichment manager 138 may be:

{  “id”: “someguid”,  “eventType”: “Device_Heartbeat”,  “eventTime”:“2018-01-27T00:00:00+00:00”  “eventValue”: 1,  “deviceID”: “someguid” }

An example of an enriched event generated by the enrichment manager 138may be:

{  “id”: “someguid”,  “eventType”: “Device_Heartbeat”,  “eventTime”:“2018-01-27T00:00:00+00:00”  “eventValue”: 1,  “deviceID”: “someguid”, “buildingName”: “Building-48”,  “buildingID”: “SomeGuid”,  “panelID”:“SomeGuid”,  “panelName”: “Building-48-Panel-13”,  “cityID”: 371, “cityName”: “Milwaukee”,  “stateID”: 48,  “stateName”: “Wisconsin(WI)”,  “countryID”: 1,  “countryName”: “United States” }

By receiving enriched events, an application of the applications 110 canbe able to populate and/or filter what events are associated with whatareas. Furthermore, user interface generating applications can generateuser interfaces that include the contextual information based on theenriched events.

The cloud platform 106 includes a platform manager 128. The platformmanager 128 can be configured to manage the users and/or subscriptionsof the cloud platform 106. For example, what subscribing building, user,and/or tenant utilizes the cloud platform 106. The platform manager 128includes a provisioning service 130 configured to provision the cloudplatform 106, the edge platform 102, and the twin manager 108. Theplatform manager 128 includes a subscription service 132 configured tomanage a subscription of the building, user, and/or tenant while theentitlement service 134 can track entitlements of the buildings, users,and/or tenants.

The twin manager 108 can be configured to manage and maintain a digitaltwin. The digital twin can be a digital representation of the physicalenvironment, e.g., a building. The twin manager 108 can include a changefeed generator 152, a schema and ontology 154, a projection manager 156,a policy manager 158, an entity, relationship, and event database 160,and a graph projection database 162.

The graph projection manager 156 can be configured to construct graphprojections and store the graph projections in the graph projectiondatabase 162. Examples of graph projections are shown in FIGS. 11-13.Entities, relationships, and events can be stored in the database 160.The graph projection manager 156 can retrieve entities, relationships,and/or events from the database 160 and construct a graph projectionbased on the retrieved entities, relationships and/or events. In someembodiments, the database 160 includes an entity-relationship collectionfor multiple subscriptions. Subscriptions can be subscriptions of aparticular tenant as described in FIG. 24.

In some embodiment, the graph projection manager 156 generates a graphprojection for a particular user, application, subscription, and/orsystem. In this regard, the graph projection can be generated based onpolicies for the particular user, application, and/or system in additionto an ontology specific for that user, application, and/or system. Inthis regard, an entity could request a graph projection and the graphprojection manager 156 can be configured to generate the graphprojection for the entity based on policies and an ontology specific tothe entity. The policies can indicate what entities, relationships,and/or events the entity has access to. The ontology can indicate whattypes of relationships between entities the requesting entity expects tosee, e.g., floors within a building, devices within a floor, etc.Another requesting entity may have an ontology to see devices within abuilding and applications for the devices within the graph.

The graph projections generated by the graph projection manager 156 andstored in the graph projection database 162 can be a knowledge graph andis an integration point. For example, the graph projections canrepresent floor plans and systems associated with each floor.Furthermore, the graph projections can include events, e.g., telemetrydata of the building subsystems 122. The graph projections can showapplication services as nodes and API calls between the services asedges in the graph. The graph projections can illustrate thecapabilities of spaces, users, and/or devices. The graph projections caninclude indications of the building subsystems 122, e.g., thermostats,cameras, VAVs, etc. The graph projection database 162 can store graphprojections that keep up a current state of a building.

In some embodiments the enrichment manager 138 can use a graphprojection of the graph projection database 162 to enrich events. Insome embodiments, the enrichment manager 138 can identify nodes andrelationships that are associated with, and are pertinent to, the devicethat generated the event. For example, the enrichment manager 138 couldidentify a thermostat generating a temperature measurement event withinthe graph. The enrichment manager 138 can identify relationships betweenthe thermostat and spaces, e.g., a zone that the thermostat is locatedin. The enrichment manager 138 can add an indication of the zone to theevent.

Furthermore, the command processor 136 can be configured to utilize thegraph projections to command the building subsystems 122. The commandprocessor 136 can identify a policy for a commanding entity within thegraph projection to determine whether the commanding entity has theability to make the command. For example, the command processor 136,before allowing a user to make a command, determine, based on the graphprojection database 162, to determine that the user has a policy to beable to make the command.

In some embodiments, the policies can be conditional based policies. Forexample, the building data platform 100 can apply one or moreconditional rules to determine whether a particular system has theability to perform an action. In some embodiments, the rules analyze abehavioral based biometric. For example, a behavioral based biometriccan indicate normal behavior and/or normal behavior rules for a system.In some embodiments, when the building data platform 100 determines,based on the one or more conditional rules, that an action requested bya system does not match a normal behavior, the building data platform100 can deny the system the ability to perform the action and/or requestapproval from a higher level system.

For example, a behavior rule could indicate that a user has access tolog into a system with a particular IP address between 8 A.M. through 5P.M. However, if the user logs in to the system at 7 P.M., the buildingdata platform 110 may contact an administrator to determine whether togive the user permission to log in.

The change feed generator 152 can be configured to generate a feed ofevents that indicate changes to the digital twin, e.g., to the graph.The change feed generator 152 can track changes to the entities,relationships, and/or events of the graph. For example, the change feedgenerator 152 can detect an addition, deletion, and/or modification of anode or edge of the graph, e.g., changing the entities, relationships,and/or events within the database 160. In response to detecting a changeto the graph, the change feed generator 152 can generate an eventsummarizing the change. The event can indicate what nodes and/or edgeshave changed and how the nodes and edges have changed. The events can beposted to a topic by the change feed generator 152.

The change feed generator 152 can implement a change feed of a knowledgegraph. The building data platform 100 can implement a subscription tochanges in the knowledge graph. When the change feed generator 152 postsevents in the change feed, subscribing systems or applications canreceive the change feed event. By generating a record of all changesthat have happened, a system can stage data in different ways, and thenreplay the data back in whatever order the system wishes. This caninclude running the changes sequentially one by one and/or by jumpingfrom one major change to the next. For example, to generate a graph at aparticular time, all change feed events up to the particular time can beused to construct the graph.

The change feed can track the changes in each node in the graph and therelationships related to them, in some embodiments. If a user wants tosubscribe to these changes and the user has proper access, the user cansimply submit a web API call to have sequential notifications of eachchange that happens in the graph. A user and/or system can replay thechanges one by one to reinstitute the graph at any given time slice.Even though the messages are “thin” and only include notification ofchange and the reference “id/seq id,” the change feed can keep a copy ofevery state of each node and/or relationship so that a user and/orsystem can retrieve those past states at any time for each node.Furthermore, a consumer of the change feed could also create dynamic“views” allowing different “snapshots” in time of what the graph lookslike from a particular context. While the twin manager 108 may containthe history and the current state of the graph based upon schemaevaluation, a consumer can retain a copy of that data, and therebycreate dynamic views using the change feed.

The schema and ontology 154 can define the message schema and graphontology of the twin manager 108. The message schema can define whatformat messages received by the messaging manager 140 should have, e.g.,what parameters, what formats, etc. The ontology can define graphprojections, e.g., the ontology that a user wishes to view. For example,various systems, applications, and/or users can be associated with agraph ontology. Accordingly, when the graph projection manager 156generates an graph projection for a user, system, or subscription, thegraph projection manager 156 can generate a graph projection accordingto the ontology specific to the user. For example, the ontology candefine what types of entities are related in what order in a graph, forexample, for the ontology for a subscription of “Customer A,” the graphprojection manager 156 can create relationships for a graph projectionbased on the rule:

-   -   Region        Building        Floor        Space        Asset

For the ontology of a subscription of “Customer B,” the graph projectionmanager 156 can create relationships based on the rule:

-   -   Building        Floor        Asset

The policy manager 158 can be configured to respond to requests fromother applications and/or systems for policies. The policy manager 158can consult a graph projection to determine what permissions differentapplications, users, and/or devices have. The graph projection canindicate various permissions that different types of entities have andthe policy manager 158 can search the graph projection to identify thepermissions of a particular entity. The policy manager 158 canfacilitate fine grain access control with user permissions. The policymanager 158 can apply permissions across a graph, e.g., if “user canview all data associated with floor 1” then they see all subsystem datafor that floor, e.g., surveillance cameras, HVAC devices, fire detectionand response devices, etc.

Referring now to FIG. 2, the cloud platform 106 and the twin manager 108processing an event received from the edge platform 102 is shown,according to an exemplary embodiment. The cloud platform 106 includes apreprocessor 202, topics 204, the enrichment manager 138, and enrichedevents 208. The twin manager 108 is shown to include the entity,relationship, and event database 160, the schema and ontology 154, andthe projection manager 156. The projection manager 156 includes thepolicy manager 158, a graph projection generator 210, and the graphprojection database 162.

Data received from the edge platform 102, or any other system describedherein, can be converted into an event if the data is not alreadyformatted as an event by the messaging manager 140. The messagingmanager 140 can provide events to the preprocessor 202. The preprocessor202 can analyze the events to make sure the events are formattedproperly. For example, the preprocessor 202 can make a call to theschema and ontology 154 of the twin manager 108 to identify the schemafor the event. The preprocessor 202 can determine whether the format ofthe event is correct based on the schema.

Furthermore, the preprocessor 202 can identify what topic the eventbelongs to, e.g., whether the event relates to a change for the graphprojection database 162 or whether the event relates to telemetry dataof a building. The preprocessor 202 can provide the event to theappropriate topics of the topics 204.

The enrichment manager 138 can be configured to enrich the events of oneor more particular topics of the topics 204. The enrichment manager 138can receive a schema for enrichment and a graph projection forenrichment. In some embodiments, the ontology received by the enrichmentmanager 138 can define enrichment rules for particular types of events,e.g., what information should be shown for particular events. Forexample, for an event of a thermostat, the rules may define thatlocation and equipment being controlled by the thermostat should beenriched into the event.

The graph projection including all of the nodes and edges that definethe contextual information associated with the event can be received bythe enrichment manager 138 from the graph projection database 162. Thereceived projection can include the information that is added into theevents as part of the enrichment. The enriched events 208 are thenprovided to the applications 110 for processing where the applications110 operate based on the original data of the event as well as thecontextual information enriched into the event.

The graph projection generator 210 is shown to receive data from theentity, relationship, and event database 160. Furthermore, the graphprojection generator 210 can receive an ontology from the schema andontology 154. The graph projection generator 210 can generate a graphprojection based on the ontology and the data received from the database160. The graph projection can be stored in the graph projection database162. Furthermore, the policy manager 158 can select different ontologiesto provide to the graph projection generator 210 and/or the enrichmentmanager 138. In this regard, based on the entity (e.g., application orsystem) that will be consuming a graph projection and/or receiving anenriched event, the policy manager 158 can select an ontology specificto the entity.

Referring now to FIG. 3, the cloud platform 106 processing events isshown, according to an exemplary embodiment. The preprocessor 202receives events and processes the events through a consumer feed filter.The consumer feed filter can filter events into particular topics forconsumption by various consumers, e.g., for particular event topics 324.In this regard, a particular application or system can create asubscription in the topic to subscription map 302 and the correspondingevents of a topic can be added to the topic of the event topics 324.

The preprocessor 202 includes a schema validator 306. The schemavalidator can make a call to the schema and ontology 154 and receive aschema or set of schemas for validating the events to determine whetherthe event is formatted in an allowed schema and/or includes the minimumfields. If the event is properly formatted (e.g., matches an approvedschema of the schema and ontology 154), the event can be provided to arouter 308. If the event is not properly formatted, the event can beadded to the malformed device tree 336. A user and/or analysis systemcan review the malformed device tree 336 to determine systemconfiguration errors. For example, the cloud platform 106 could identifyimproper graph configurations where nodes or relationships are missingwithin the graph.

The router 308 can add the event to one or more topics of the topic 204.One topic of the topics 310 is a change feed topic 310. Graph changefeed events are created by the change feed generator 152 and added tothe change feed topic 310. The topics 204 further include raw eventstopic 312, metadata topic 314, and device tree topic 316. The router canfan the event into various topics based on a type of the event.

The metadata topic 314 can include metadata 320. The metadata may bedata describing entities (e.g., equipment) and/or capabilities and/orpolicies associated with the entities. During a discovery phase that thecloud platform 106 can be configured to operate in, where equipment isdiscovered by the cloud platform 106, or during a normal operating modeof the cloud platform 106, metadata events can be added to the metadatatopic 314 to update the entities, relationships, and events of thedatabase 160, e.g., build up the graph projections.

In some embodiments, all events are added into the raw event topic. Insome embodiments, if an event relates to how the graph is represented,the event is added into the metadata topic 314. In some embodiments, ifthe event represents a new device or set of devices, the device is addedto the device tree topic 316. In some embodiments, the device tree dataof the device tree topic 316 can be a type of event that describes anobject or asset discovered by the cloud platform 106 that contains therelationship of that object to other objects of similar context

A raw event 318 of the raw events topic 312 can be provided to theenrichment manager 206 for enrichment. The enrichment manager 206 canreceive a graph projection from the graph projection database 162 andenrich the raw event 318 based on context of the graph projection. Insome embodiments, the enrichment manager 206 can enrich the raw event318 based on one or more user rules. For example, the rules could be toenrich indications of assets shown within a field of view of a camerawhere the event is a frame or set of frames captured by the camera. Theenriched events can be enriched based on destination. For example, theevent can be enriched according to the system that will be receiving theevent. In this regard, the event can be enriched multiple differenttimes for multiple different receiving systems.

Enrichment may help systems operate quickly. For example, a person mayscan a badge at a door. An application may look up the user of the badgewith the badge number. Furthermore, the application may look up whatequipment and what place the scanner is associated with. However, byperforming multiple searches, the processing of the applications may beslow. However, with the enrichment of the enrichment manager 206, atelemetry event such as scanning a door badge can add floor indications,user identifications, etc. so that the receiving application can operateon the event and contextual information without needing to search forand/or retrieve the contextual information.

The enriched event can be added to the event topics 324. The eventtopics 324 can be subscribed to by various systems. For example, a graphprojection processor 326 can make updates to projections of the graphprojection database 162 based on the enriched event. For examplestelemetry data could be added to the graph projection database 162,statuses of equipment could be added to the graph projection database162, etc. The persist service 328 can persist the enriched events in anevents database 332. Furthermore, a publisher 330 can provide theenriched events to the applications 110, e.g., to particularapplications subscribed to the enriched events.

Referring now to FIG. 4, the twin manager 108 generating projections andoperating with components of the cloud platform 106 to enrich events isshown, according to an exemplary embodiment. The twin manager 108includes an event manager 404. The event manager can receive data from auser device and/or another system. The event manager 404 can receive anaddition of an event type, an addition of an event stream, a new event,and/or a new event subscription. Based on the received information, theevent manager 404 can be configured to update the topic to subscriptionmap 408. Furthermore, if the received information indicates changes tothe graph projections of the graph projection database 162, the eventmanager 404 can be configured to generate a change event for a changefeed.

The twin manager 108 includes a query manager 402. The query manager 402can receive a query or a post from a user device or another system. Thequery manager 402 can be configured to query the entity, relationship,and/or event database 160 based on the query. An ontology received fromthe schema and ontology 154 can define the query that the query manager402 makes to the database 160. In some embodiments, the query manager402 can be configured to upsert new entities, relationships, and/orevents into the database 160. In some embodiments, the query manager 402constructs a query or determines whether to upsert information to thedatabase 160 based on an access control list received from the policymanager 158. In this regard, the entity requesting information through aquery or sending a post of new information can be verified for havingthe proper access policy by the policy manager 158 and the query manager402.

The policy manager 158 is shown to receive projections from the graphprojection generator 210. In some embodiments, the policy manager 158can receive the projections from the graph projection database 162. Thepolicy manager 158 can be configured to receive a request for access toinformation and can review the graph to determine whether the requestingentity has the proper access to the information. The policy manager 158can serve access control lists determined from the graph projections tothe query manager 402. The policy manager 158 can serve the accesscontrol list to the schema and ontology 154 for use in providing anontology to the enrichment manager 206 and/or for user in determiningprojection rules for the graph projection generator 210.

Referring now to FIG. 5, a preprocessing workflow 500 performed by thecloud platform 106 to preprocess events is shown, according to anexemplary embodiment. Events can be received by the platform 106. Thecloud platform 106 can filter the events in step 502. The events can befiltered into schema discovery, e.g., a new message schema, forfiltering into an existing schema message category. Furthermore, in step502, the cloud platform 106 can add subscription identifier and entityinformation to the event. For example, the subscription identifier canbe looked up in step 504 via the topic to subscription map 408. Theentity information can indicate the entity related to the event, e.g.,the entity that created the event. For example, a thermostat, theentity, may have generated a temperature measurement, the event.

If the message is for a schema discovery (step 506), the cloud platform106 can post the schema used in the message in the schema and ontology154 or alternatively proceed to step 512. In step 508, the cloudplatform 106 can lookup valid message schemas from the schema andontology 154. In step 512, the cloud platform 106 can determine whetherthe schema of the event is valid or invalid based on the valid messageschemas. In step 514, if the schema is invalid, the event can be addedto an invalid schema deadletter where invalid schema events are stored.If the schema is valid, the event can be routed to message topics basedon a type of the message in step 516, e.g., whether the event ismetadata, a raw event, etc.

Referring now to FIG. 6, a discovery workflow 600 discovering newentities from metadata 314 and a device tree 322 that is performed bythe cloud platform 106 is shown, according to an exemplary embodiment.The cloud platform 106 can receive the metadata 314 and start a processtimer in step 602. In step 604, the cloud platform 106 can transform andmap device, type, and capabilities. The cloud platform 106 can referencea missing type to schema mapping. In step 610, the cloud platform 106can look up a reference mapping for the metadata, definitions ofentities for the metadata, a tenant associated with the metadata, and/orother information of an entity relationship collection. In step 608, thenew device types can be persisted as metadata 616 and added to ametadata device table 614.

In step 628, the cloud platform 106 can start a process timer inresponse to receiving the device tree 322. The device tree 322 can beanalyzed to determine what action, e.g., verb, operation, or subjectincluded within the device tree 322 is to be performed. The action maybe an insert, update, or delete command for the graph projections. Instep 618, the cloud platform 106 can transform or map the device treebased on metadata stored in the device metadata 616. In step 634, thecloud platform 106 can evaluate the process and determine if a messagehas already been processed. In step 620 the processor cost can becalculated and in step 622 the event can be logged in the processing log613. In step 636 the new data for insertion, updating, and/or deletioncan be posted.

In response to receiving the device tree 322, the cloud platform 106 canstart a process timer in step 628. The cloud platform 106 can analyzethe device tree 322 for a verb, operation, and/or subject to constructan insert command, an update command, and/or a delete command 632.

Referring now to FIG. 7, a projection workflow 700 performed by the twinmanager 108 is shown, according to an exemplary embodiment. In step 702,the twin manager 108 can receive a change feed event from the changefeed generator 152. Based on the change feed event, in step 704, thetwin manager 108 can generate a graph projection and store the graphprojection. The twin manager 108 can edit existing graph projections ofthe graph projection database 162 based on the change feed event. Thetwin manager 108 can replace an existing graph projection of the graphprojection database 162 with a new graph projection created responsiveto receiving the change feed event.

The twin manager 108 can receive a query from the query manager 706. Thequery may be a query for information of a graph projection and/or aquery for a graph projection itself The query can originate from arequesting application, system, or user device. The twin manager 108can, in step 708, retrieve a graph projection based on a policy for therequesting system.

The twin manager 108 can retrieve policies from a policy database 161 todetermine which graph projection the querying system has access to. Inresponse to retrieving the appropriate graph projection from the graphprojection database 162, the twin manager 108 can construct a queryresponse including the specific information from the graph projectionand/or the graph projection itself. The twin manager 108 can return thequery response to the query manager 706.

Referring now to FIG. 8, an enrichment workflow 800 performed by thecloud platform 106 enriching events with contextual information isshown, according to an exemplary embodiment. The cloud platform 106receives an internal event 802, metadata 320, a device tree 322, and araw event 314. The internal event 802 may be an event created by thebuilding data platform 100 requiring enrichment. Each data elementreceived can be enriched according to the workflow 800.

In step 806, in response to receiving an event, a process timer can bestarted. In step 808, the cloud platform 106 can get an event type forthe event from an event type storage 812 and a projection type from aprojection type storage 814. In this regard, a projection type specificto the event can be retrieved. The specific projection identified can beretrieved in step 810 and entities and relationships specific forenriching the event can be retrieved from the graph projection. Based onthe entities and relationships, a custom enrichment can be generated instep 816 for the event.

In some embodiments, some events may not be associated with any eventtype and/or projection type. In response to identifying an event thatcannot be enriched, the cloud platform 106 can add the event to a deadletter 820. The dead letter 820 can be reviewed by users and/or systemsto identify errors in the operation of the cloud platform 106 and/orissues with the systems creating the events.

Referring now to FIG. 9, a command processing workflow 900 performed bythe cloud platform 106 where commands are sent to devices or arecommunicated to an external system via a connection broker is shown,according to an exemplary embodiment. The cloud platform 106 can receivean internal command 902 and/or an external command 904. The internalcommand 902 can be a command generated by a component of the buildingdata platform 100. The external command 904 can be a command generatedby an external device or system, e.g., the user device 176.

In step 906, the internal command 902 and/or the external command 904can be received and a process timer started. In step 908, the cloudplatform 106 can authorize the command to determine whether the entityrequesting the command is authorized to perform the command. Forexample, the cloud platform 106 can search a graph projection of thegraph projection database 162 for policies and capabilities to determinewhether the requesting entity has access to make the command that theentity is making.

If the command is not authorized, in step 910 the event can be logged ina processing log 912. In step 914, the cloud platform 106 can determinewhether the command is a command for a device of the building subsystems122, e.g., a command to device (C2D) command or a command for anexternal system that will be handled via a connector, a command toconnector (C2C) command. In response to the command being a C2D command,the cloud platform 106 can enqueue the message to be sent to a devicevia a device hub in step 916. The cloud platform 106 can consult a graphprojection to identify the device hub responsible for handling commandsfor the device.

If the command is a C2C command, the cloud platform 106 can select aconnection broker 918 in step 922. The connection broker 918 can be acomponent configured to communicate and integrate with external systems,e.g., the external system 920. For example, an office program suite, avirtual meeting platform, an email server, etc. can all integrate withthe building data platform 100 via the connection broker 918. The cloudplatform 106 can select the appropriate connection broker for thecommand by searching a graph projection of the graph projection database162.

Referring now to FIG. 10, a messaging workflow 1000 performed by thecloud platform 106 where messages of building subsystems 122 arereceived via the edge platform 102 and commands for the buildingsubsystems 122 are communicated to the building subsystems 122 via theedge platform 102 is shown, according to an exemplary embodiment. Thecloud platform 106 can receive data events from building subsystems 122via an edge platform 102 through device hubs 1002 and 1004 specific todevices of the building subsystems 122.

The device hubs 1002 and 1004 can post events into topics 1006 and 1008.A source identifier 1010 subscribed to the topics 1006 and 1008 can lookup an identifier of the device hub based on an identifier of the deviceand post the event into a data feed topic 1011 associated with thedevice hub in a device hub identifier mapping to device identifier 1012.An event handler 1018 can provide the event to the preprocessor 202.

The C2D command of the command processing workflow 900. The command canbe posted in a C2D message topic 1014. A command processor 1016subscribed to the C2D message topic 1014 can read the C2D messages andprovide the C2D commands to the appropriate device topics, e.g., topic1006 or topic 1008. The device hubs 1002 and/or 1004 can pick up the C2Dcommands and operate the building subsystems 122 via the C2D command.

Referring now to FIG. 11, a graph projection 1100 of the twin manager108 including application programming interface (API) data, capabilitydata, policy data, and services is shown, according to an exemplaryembodiment. The graph projection 1100 includes nodes 1102-1140 and edges1150-1172. The nodes 1102-1140 and the edges 1150-1172 are definedaccording to the key 1101. The nodes 1102-1140 represent different typesof entities, devices, locations, points, persons, policies, and softwareservices (e.g., API services). The edges 1150-1172 representrelationships between the nodes 1102-1140, e.g., dependent calls, APIcalls, inferred relationships, and schema relationships (e.g., BRICKrelationships).

The graph projection 1100 includes a device hub 1102 which may representa software service that facilitates the communication of data andcommands between the cloud platform 106 and a device of the buildingsubsystems 122, e.g., door actuator 1114. The device hub 1102 is relatedto a connector 1104, an external system 1106, and a digital asset “DoorActuator” 1108 by edge 1150, edge 1152, and edge 1154.

The cloud platform 106 can be configured to identify the device hub1102, the connector 1104, the external system 1106 related to the dooractuator 1114 by searching the graph projection 1100 and identifying theedges 1150-1154 and edge 1158. The graph projection 1100 includes adigital representation of the “Door Actuator,” node 1108. The digitalasset “Door Actuator” 1108 includes a “DeviceNameSpace” represented bynode 1108 and related to the digital asset “Door Actuator” 1108 by the“Property of Object” edge 1156.

The “Door Actuator” 1114 has points and timeseries. The “Door Actuator”1114 is related to “Point A” 1116 by a “has_a” edge 1160. The “DoorActuator” 1114 is related to “Point B” 1118″ by a “has_A” edge 1158.Furthermore, timeseries associated with the points A and B arerepresented by nodes “TS” 1120 and “TS” 1122. The timeseries are relatedto the points A and B by “has_a” edge 1164 and “has_a” edge 1162. Thetimeseries “TS” 1120 has particular samples, sample 1110 and 1112 eachrelated to “TS” 1120 with edges 1168 and 1166 respectively. Each sampleincludes a time and a value. Each sample may be an event received fromthe door actuator that the cloud platform 106 ingests into the entity,relationship, and event database 160, e.g., ingests into the graphprojection 1100.

The graph projection 1100 includes a building 1134 representing aphysical building. The building includes a floor represented by floor1132 related to the building 1134 by the “has_a” edge from the building1134 to the floor 1132. The floor has a space indicated by the edge“has_a” 1170 between the floor 1132 and the space 1130. The space hasparticular capabilities, e.g., is a room that can be booked for ameeting, conference, private study time, etc. Furthermore, the bookingcan be canceled. The capabilities for the floor 1132 are represented bycapabilities 1128 related to space 1130 by edge 1180. The capabilities1128 are related to two different commands, command “book room” 1124 andcommand “cancel booking” 1126 related to capabilities 1128 by edge 1184and edge 1182 respectively.

If the cloud platform 106 receives a command to book the spacerepresented by the node, space 1130, the cloud platform 106 can searchthe graph projection 1100 for the capabilities for the 1128 related tothe space 1128 to determine whether the cloud platform 106 can book theroom.

In some embodiments, the cloud platform 106 could receive a request tobook a room in a particular building, e.g., the building 1134. The cloudplatform 106 could search the graph projection 1100 to identify spacesthat have the capabilities to be booked, e.g., identify the space 1130based on the capabilities 1128 related to the space 1130. The cloudplatform 106 can reply to the request with an indication of the spaceand allow the requesting entity to book the space 1130.

The graph projection 1100 includes a policy 1136 for the floor 1132. Thepolicy 1136 is related set for the floor 1132 based on a “To Floor” edge1174 between the policy 136 and the floor 1132. The policy 1136 isrelated to different roles for the floor 1132, read events 1138 and sendcommand 1140. The policy 1136 is set for the entity 1103 based on hasedge 1151 between the entity 1103 and the policy 1136.

The twin manager 108 can identify policies for particular entities,e.g., users, software applications, systems, devices, etc. based on thepolicy 1136. For example, if the cloud platform 106 receives a commandto book the space 1130. The cloud platform 106 can communicate with thetwin manager 108 to verify that the entity requesting to book the space1130 has a policy to book the space. The twin manager 108 can identifythe entity requesting to book the space as the entity 1103 by searchingthe graph projection 1100. Furthermore, the twin manager 108 can furtheridentify the edge has 1151 between the entity 1103 and the policy 1136and the edge 1178 between the policy 1136 and the command 1140.

Furthermore, the twin manager 108 can identify that the entity 1103 hasthe ability to command the space 1130 based on the edge 1174 between thepolicy 1136 and the edge 1170 between the floor 1132 and the space 1130.In response to identifying the entity 1103 has the ability to book thespace 1130, the twin manager 108 can provide an indication to the cloudplatform 106.

Furthermore, if the entity makes a request to read events for the space1130, e.g., the sample 1110 and the sample 1112, the twin manager 108can identify the edge has 1151 between the entity 1103 and the policy1136, the edge 1178 between the policy 1136 and the read events 1138,the edge 1174 between the policy 1136 and the floor 1132, the “has_a”edge 1170 between the floor 1132 and the space 1130, the edge 1168between the space 1130 and the door actuator 1114, the edge 1160 betweenthe door actuator 1114 and the point A 1116, the “has_a” edge 1164between the point A 1116 and the TS 1120, and the edges 1168 and 1166between the TS 1120 and the samples 1110 and 1112 respectively.

Referring now to FIG. 12, a graph projection 1200 of the twin manager108 including application programming interface (API) data, capabilitydata, policy data, and services is shown, according to an exemplaryembodiment. The graph projection 1200 includes the nodes and edgesdescribed in the graph projection 1100 of FIG. 11. The graph projection1200 includes a connection broker 1254 related to capabilities 1128 byedge 1298 a. The connection broker 1254 can be a node representing asoftware application configured to facilitate a connection with anothersoftware application. In some embodiments, the cloud platform 106 canidentify the system that implements the capabilities 1128 by identifyingthe edge 1298 a between the capabilities 1128 and the connection broker1254.

The connection broker 1254 is related to an agent that optimizes a space1256 via edge 1298 b. The agent represented by the node 1256 can bookand cancel bookings for the space represented by the node 1130 based onthe edge 1298 b between the connection broker 1254 and the node 1256 andthe edge 1298 a between the capabilities 1128 and the connection broker1254.

The connection broker 1254 is related to a cluster 1208 by edge 1298 c.Cluster 1208 is related to connector B 1201 via edge 1298 e andconnector A 1206 via edge 1298 d. The connector A 1206 is related to anexternal subscription service 1204. A connection broker 1210 is relatedto cluster 1208 via an edge 1211 representing a rest call that theconnection broker represented by node 1210 can make to the clusterrepresented by cluster 1208.

The connection broker 1210 is related to a virtual meeting platform 1212by an edge 1254. The node 1212 represents an external system thatrepresents a virtual meeting platform. The connection broker representedby node 1210 can represent a software component that facilitates aconnection between the cloud platform 106 and the virtual meetingplatform represented by node 1212. When the cloud platform 106 needs tocommunicate with the virtual meeting platform represented by the node1212, the cloud platform 106 can identify the edge 1254 between theconnection broker 1210 and the virtual meeting platform 1212 and selectthe connection broker represented by the node 1210 to facilitatecommunication with the virtual meeting platform represented by the node1212.

A capabilities node 1218 can be connected to the connection broker 1210via edge 1260. The capabilities 1218 can be capabilities of the virtualmeeting platform represented by the node 1212 and can be related to thenode 1212 through the edge 1260 to the connection broker 1210 and theedge 1254 between the connection broker 1210 and the node 1212. Thecapabilities 1218 can define capabilities of the virtual meetingplatform represented by the node 1212. The capabilities may be an invitebob command represented by node 1216 and an email bob commandrepresented by node 1214. The capabilities 1218 can be linked to a node1220 representing a user, Bob. The cloud platform 106 can facilitateemail commands to send emails to the user Bob via the email servicerepresented by the node 1204. Furthermore, the cloud platform 106 canfacilitate sending an invite for a virtual meeting via the virtualmeeting platform represented by the node 1212.

The node 1220 for the user Bob can be associated with the policy 1136via the “has” edge 1264. Furthermore, the node 1220 can have a “checkpolicy” edge 1266 with a portal node 1224. The portal node 1224 has anedge 1268 to the policy node 1136. The portal node 1224 has an edge 1223to a node 1226 representing a user input manager (UIM). The UIM node1226 has an edge 1223 to a device API node 1228. The door actuator node1114 has an edge 1274 to the device API node 1228. The door actuator1114 has an edge 1235 to the connector virtual object 1234. The deviceAPI node 1228 can be an API for the door actuator 1114.

The device API node 1228 is related to a transport connection broker1230 via an edge 1229. The transport connection broker 1230 is relatedto a device hub 1232 via an edge 1278. The device hub represented bynode 1232 can be a software component that hands the communication ofdata and commands for the door actuator 1114. The cloud platform 106 canidentify where to store data within the graph projection 1200 receivedfrom the door actuator by identifying the nodes and edges between thepoints 1116 and 1118 and the device hub node 1232. Similarly, the cloudplatform 1208 can identify commands for the door actuator that can befacilitated by the device hub represented by the node 1232, e.g., byidentifying edges between the device hub node 1232 and an open door node1252 and an lock door node 1250. The door actuator 114 has an edge “hasmapped an asset” 1180 between the node 1114 and a capabilities node1248. The capabilities node 1248 and the nodes 1252 and 1250 are linkedby edges 1296 and 1294.

The device hub 1232 is linked to a cluster 1236 via an edge 1284. Thecluster 1236 is linked to connector A 1240 and connector B 1238 by edges1286 and the edge 1288. The connector A 1240 and the connector B 1238 islinked to an external system 1244 via edges 1288 and 1290. The externalsystem 1244 is linked to a door actuator 1242 via an edge 1292.

Referring now to FIG. 13, a graph projection 1300 of the twin manager108 including equipment and capability data for the equipment is shown,according to an exemplary embodiment. The graph projection 1300 includesnodes 1302-1356 and edges 1260-1398 f. The cloud platform 106 can searchthe graph projection 1300 to identify capabilities of different piecesof equipment.

A building 120 node 1304 represents a particular building that includestwo floors. A floor 1 node 1302 is linked to the building 120 node 1304via edge 1360 while a floor 2 node 1306 is linked to the building 120node 1304 via edge 1362. The floor 2 includes a particular room 2023represented by edge 1364 between floor 2 node 1306 and room 2023 node1308. Various pieces of equipment are included within the room 2023. Alight represented by light node 1316, a bedside lamp node 1314, abedside lamp node 1312, and a hallway light node 1310 are related toroom 2023 node 1308 via edge 1366, edge 1372, edge 1370, and edge 1368.

The light represented by light node 1316 is related to a light connector1326 via edge 1384. The light connector 1326 is related to multiplecommands for the light represented by the light node 1316. The commandsmay be a brightness setpoint 1324, an on command 1326, and a huesetpoint 1328. The cloud platform 106 can receive a request to identifycommands for the light represented by the light 1316 and can identifythe nodes 1324-1328 and provide an indication of the commandsrepresented by the node 1324-1328 to the requesting entity. Therequesting entity can then send commands for the commands represented bythe nodes 1324-1328.

The bedside lamp node 1314 is linked to a bedside lamp connector 1381via an edge 1313. The connector 1381 is related to commands for thebedside lamp represented by the bedside lamp node 1314 via edges 1392,1396, and 1394. The command nodes are a brightness setpoint node 1332,an on command node 1334, and a color command 1340. The hallway light1310 is related to a hallway light connector 1346 via an edge 1398 d.The hallway light connector 1346 is linked to multiple commands for thehallway light node 1310 via edges 1398 g, 1398 f, and 1398 e. Thecommands are represented by an on command node 1352, a hue setpoint node1350, and a light bulb activity node 1348.

The graph projection 1300 includes a name space node 1322 related to aserver A node 1318 and a server B node 1320 via edges 1374 and 1376. Thename space node 1322 is related to the bedside lamp connector 1381, thebedside lamp connector 1344, and the hallway light connector 1346 viaedges 1382, 1380, and 1378.

Referring now to FIG. 14, a block diagram of a user interaction manager1402 that handles user queries and requests is shown, according to anexemplary embodiment. The user interaction manager 1402 can be acomponent of the cloud platform 106. The user interaction manager 1402in some embodiments, is a system separate from the cloud platform 106.The user interaction manager 1402 includes processor(s) 1404 andmemories 1406. The processor(s) 1404 and the memories 1406 can besimilar to, or the same as, the processors and memories described withreference to FIG. 1.

The user interaction manager 1402 receives an APPLE query from the userdevice 176. The user interaction manager 1402 can be configured to querythe graph based on the APPLE query and generate a query response basedon the APPLE query and return the query response to the user device 176.Although the user device 176 is shown in FIG. 14 to send the APPLE queryto the user interaction manager 1402 and receive the query response, anycomputing system can send a query and receive a query response from theuser interaction manager 1402, e.g., the applications 110, the buildingsubsystems 122, etc.

The APPLE query can include an asset parameter 1410, a point parameter1412, a people parameter 1414, a location parameter 1416, and an eventparameter 1418 that a query parser 1408 of the user interaction manager1402 can utilize in querying a graph projection. The graph parser 1408can query the graph with entities 1420 and/or relationships 1426 whichcan indicate capabilities 1434, commands 1436, schema type 1438 and/orentity relationship history 1440.

The user interaction manager 1402 can analyze event type registration1422, subscriptions to events 1424, filtering for relevant events 1428,validating events 1430, identifying event history 1442, and performevent enrichment 1444. For example, events received at an ingress 1454from a device hub 1452 can be validated according to a schema. If thevalidator 1430 determines that the entity is not of a valid schema, thevalidator 1430 can add the event to a dead letter 1456.

A policy evaluator 1432 of the user interaction manager 1402 candetermine whether the user of the user device 176 (or another system orapplication) has the appropriate policies to view information of thegraph and/or make the commands indicated by the user device 176. Thepolicy evaluator 1432 can determine whether or not to implement acommand based on command policies for the user device 176 which may beindicated by a graph projection. Furthermore, the policy evaluator 1432can determine whether or not to respond to a query based on whether theuser device 176 has access to view the queried information. The policyevaluator 1432 can be configured to generate a policy projection 1476.Data access 1446 and 1448 can provide access to assets, points, people,locations, and events. The data access 1446 and/or 1448 can retrievedata of the building subsystems 122 via the connector 1474 and/or viathe database 1468 including entities 1472 and relationships 1470. A dataretention layer 1450 can retain a record of all queries and queryresponses.

The user interaction manager 1402 can provide a UI for the provisioningservice 130 to provision tenants. A tenant management system can providetenant and/or subscription services for generating new customersubscriptions, e.g., subscriptions for a tenant of a building.Similarly, the provisioning service 130 can receive policies and/ordevice management commands from the tenant management system 1478 forcreating a graph projection for the customer subscription.

Referring now to FIG. 15, a process 1500 of a security dashboard 1502communicating with the building data platform 100 to review informationabout equipment and command the equipment is shown, according to anexemplary embodiment. The process 1500 can be performed by the buildingdata platform 100. In some embodiments, the twin manager 108, theapplications 110, and/or the cloud platform 106 can perform the process1500. In FIG. 15, a security dashboard 1502, the user interactionmanager 1402, a cache 1504, a device interface manager 1506, the policymanager 158, and a transport manager 1510 are shown to perform theprocess 1500. The aforementioned components can be components of theapplications 110, the twin manager 108, and the cloud platform 106.

In step 1512, the security dashboard 1502 can receive a command from auser to look at doors with active alarms on a particular floor, a secondfloor of a building. In some embodiments, the security dashboard 1502 isan application run by the applications 110. In some embodiments, theuser interacts with the security dashboard 1502 via the user device 176.

In step 1514, the security dashboard 1502 queries the user interactionmanager 1402 for assets and events, in particular, doors (assets) withan active alarm (event) on a second floor (asset). In step 1516, theuser interaction manager 1402 can get read permissions to an entity andrelationship collection from the policy manager 158. The policy manager158 can determine which entities and/or events the user has access tobased on policies indicated by a graph projection of the graphprojection database 162. The policy manager 158 can determine whetherthe user has access to read entities and/or relationships.

In response to the user having access to read the entities and/orrelationships, the policy manager 158 can send a granted indication instep 1518 to the user interaction manager 1402. In step 1520, the userinteraction manager can get read permissions for events on the secondfloor from the policy manager 158. The policy manager 158 can determinewhether the user has access to the events of the second floor bysearching a graph projection and can respond to the user interactionmanager 1402 with a granted message in step 1522 in response todetermining that the user has access to the events of the second floor.

Responsive to receiving the access to read the entities, relationships,and events of the second floor, the user interaction manager 1402 canread the entities relationships, and events from the cache 1504. In someembodiments, the user interaction manager 1402 can read the entities,relationships, and events from a graph projection in step 1524.

In step 1526, the cache 1504 can return the requested data of the step1534 to the user interaction manager 1402. In step 1528, the userinteraction manager 1402 can return the filtered assets withcapabilities of the assets. For example, all doors on the second floorcan be returned in step 1528 along with a capability to command eachdoor to lock or unlock. In step 1530, the security dashboard 1502 candisplay doors with active alarms on the second floor along withcapabilities of the doors.

In step 1532, a user can click a particular door displayed in the step1530, e.g., a door 13, and select the command to lock the door. In step1534, the security dashboard 1502 can send a lock door command for door13 to the user interaction manager 1402. The user interaction manager1402 can get a send command permission for the door 13 from the policymanager 158 in step 1536. The policy manager 158 can determine, based ona graph projection, whether the user has access to command the door 13to lock. In response to detecting that the user does have a policy tolock the door 13, the policy manager 158 can send a granted message tothe device interface manager 1506 in step 1538. The device manager 1506can send the command to lock the door 13 to a transport manager 1510 insteps 1540-1546. The transport manager 1510 can facilitate the commandto lock the door 13. Before implementing the command, the deviceinterface manager 1506 can communicate with the policy manager 158 toverify that the permission to command the door and the policy manager158 can send a granted message in step 1544 to the device interfacemanager 1506 in response to determining that that the permission exists.

An acknowledge message can be sent to the device interface manager 1506in step 1548 by the transport manager 1510 indicating that the commandhas been sent. The device interface manager 1506 can send a successmessage 1550 to the user interaction manager 1402. The user interactionmanager 1402 can send a success message to the security dashboard 1502in step 1552. The security dashboard 1502 can display a message to theuser that the command has been successfully sent to the door 13 in step1554.

Referring now to FIG. 16, a flow diagram of a process 1600 where anevent of building equipment is enriched with contextual information of agraph that can be performed by the cloud platform 106 is shown,according to an exemplary embodiment. In some embodiments, the cloudplatform 106 can be configured to perform the process 1600. Furthermore,any computing device or system described herein can be configured toperform the process 1600.

In step 1602, the cloud platform 106 receives an event from buildingequipment or services. In some embodiments, the cloud platform 106receives non-event data, e.g., a stream of timeseries data, a message,etc. and normalizes the data into event data. The event can include oneor more parameters, e.g., a data value (e.g., a temperature, anequipment status, etc.), a time at which the event occurred, etc. Insome embodiments, the cloud platform 106 receives the event from anevent source, for example, cloud data, NC4, a weather data service, thecloud platform 106 itself (e.g., an event, an enriched event, etc.),and/or any other system or device.

In step 1604, the cloud platform 106 can identify one or more entitiesand/or one or more relationships of a graph related to the event. Theentities could be an indication of a location of the event (e.g., whatroom, what floor, what building the event occurred in), the buildingentities that consume the data of the event, other entities affected bythe event (e.g., a temperature setpoint change of one room affecting thetemperature of an adjacent room), etc. The relationships can indicatehow the event is related to the entities. For example, a relationship,“isLocatedIn,” could be added to indicate that the sensor producing theevent is located in a specific space.

In some embodiments, the cloud platform 106 identifies the one or moreentities and the one or more relationships from a graph projection. Thegraph projection can be a graph projection specific to a particularsubscriber (e.g., user or organization) of the cloud platform 106. Insome embodiments, the cloud platform 106 receives the graph projectionfrom the graph projection database 162.

In step 1606, the cloud platform 106 generates an enriched event withthe event and the one or more entities and the one or more relationshipsof the step 1604. The cloud platform 106 can add multiple attributes tothe event based on the entities and the relationships. In someembodiments, the cloud platform 106 generates an enriched event packageincluding all of the data of the enriched event and the one or moreentities and one or more relationships identified in the step 1604.

In step 1608, the cloud platform 106 can provide the enriched event ofthe step 1066 to one or more applications configured to operate based onthe enriched event. In some embodiments, the applications 110 canreceive the enriched event and operate based on the data of the eventand the contextual information (e.g., the entities and relationships)enriching the event. For example, for an application that controls thetemperature of a space, an enriched event can include a temperaturemeasurement of the space in addition to an identification of the spaceand the VAV box for the space. The application can generate a commandfor the VAV box based on the temperature measurement and communicate thetemperature measurement to the identified VAV box of the enriched event.

Referring now to FIG. 17, a process 1700 where a change feed of eventsthat record modifications to a graph that can be performed by the twinmanager 108 is shown, according to an exemplary embodiment. The twinmanager 108 can be configured to perform the process 1700. In someembodiments, components of the twin manager 108 are configured toperform the process 1700, for example, the change feed generator 152and/or the graph projection database 162. In some embodiments, anycomputing device described herein is configured to perform the process1700.

In step 1702, the twin manager 108 receives one or more changes to agraph. The changes may modify one or more nodes or one or more edges ofthe graph. For example, the changes may be to add a new node or edge,delete an existing node or edge, or modify an existing node or edge ofthe graph. In some embodiments, the modification is received by the twinmanager 108 from the user device 176, e.g., the user provides the twinmanager 108 with a modification to a graph. In some embodiments, themodification is received as an event indicating a change to the graph,e.g., event is metadata 320 or the device tree 322.

In step 1704, the twin manager 108 generates a change feed eventrecording the changes modifying the one or more nodes and/or the one ormore edges. The event can be a data package of information including anevent time, a time at which the event occurred. In some embodiments, theevent includes an indication of how the graph has changed, e.g., whatnodes and/or edges of the graph have changed and how those nodes and/oredges have changed. The twin manager 108 can implement the changes ofstep 1702 to the graph and also generate an event recording the changeto the graph.

In step 1706, the twin manager 108 can add the event to a change feed.The change feed can include multiple change events for different changesto the graph. The change feed may be a topic that some applicationsand/or systems subscribe to, e.g., the applications 110. In step 1706,one or more applications that operate based on the graph can receive thechange feed. In this regard, the applications and/or systems can receivethe change feed event and update their storage of the graph based on thechange feed. This can allow the application and/or system to updatetheir graph without receiving the entire graph, just an indication ofthe change. Furthermore, the twin manager 108 and/or any other systemcan generate the graph at one or more different times based on theevents of the change feed to track the configuration of the graph atmultiple different times.

Referring now to FIG. 18, a flow diagram of a process 1800 where a graphidentifying capabilities of a piece of equipment is used to operate thepiece of equipment that can be performed by the cloud platform 106 isshown, according to an exemplary embodiment. In some embodiments, thecloud platform 106 is configured to perform the process 1800. In someembodiments, a component of the cloud platform 106, e.g., the commandprocessor 136 is configured to perform the process 1800. Any computingdevice described herein can be configured to perform the process 1800.

In step 1802, the cloud platform 106 can identify a capability of apiece of equipment based on a graph of nodes and edges where a firstnode of the nodes represents the capability and a second node of thenodes represents the piece of equipment where one or more edges relatethe first node and the second node. In some embodiments, the cloudplatform 106 may receive a request for information about thecapabilities of a piece of equipment, e.g., from a user request via theuser device 176 or from a device of the building subsystems 122 (e.g., athermostat may request to control a VAV box). The cloud platform 106 canidentify the capabilities, the operational commands that the piece ofequipment can perform by identifying capability nodes related to a nodeof the piece of equipment through one or more edges and/or nodes betweenthe nodes for the capabilities and the node for the piece of equipment.The cloud platform 106 can analyze a graph projection received from thetwin manager 108 to identify the capabilities.

In some embodiments, an entity can have capabilities originating fromdifferent systems. For example, a room could be an entity with acapability for temperature control, based on HVAC systems for the room.The room could also have a booking capability to reserve the room basedon a room booking and/or meeting scheduling system.

In step 1804, the cloud platform 106 can receive a command to operatethe piece of equipment based on the capability identify from the graphin the step 1802. In some embodiments, the cloud platform 106communicates the capability to the requesting entity, e.g., the userdevice 176, the applications 110, a device of the building subsystems122, etc. The requesting entity can review the capability and issue acommand for the capability.

In step 1806, the cloud platform 106 can provide the command to thepiece of equipment. In some embodiments, the cloud platform 106identifies a software component configured to manage messaging for thepiece of equipment. The cloud platform 106 may identify the softwarecomponent from the graph. For example, a node of the graph may representthe software component and one or more edges or nodes may relate thesoftware component node and the node representing the piece ofequipment. The cloud platform 106 can identify the software component byidentifying the edges and/or nodes relating the software component nodeand the node representing the piece of equipment. The cloud platform 106can provide the command to the software component to handle commandingthe piece of equipment.

Referring now to FIG. 19, a process 1900 where the cloud platform 106operates different services related by a graph is shown, according to anexemplary embodiment. In some embodiments, the process 1900 is performedby the cloud platform 106. In some embodiments, any computing devicedescribed herein is configured to perform the process 1900.

In step 1902, the cloud platform 106 receives an indication to performan action for an entity. The action could be controlling a piece ofbuilding equipment. Implementing a command with an external system,e.g., generating a virtual meeting via a virtual meeting platform, sendan email via an email service, etc.

In step 1904, the cloud platform 106 can identify a service configuredto perform the action based on a graph including nodes and edges. Forexample, if the command is to send an email, the cloud platform 106 mayidentify an email service by identifying an email service node of thegraph. If the action is to command a piece of building equipment tooperate, the cloud platform 106 could identify a node of the graphrepresenting a device hub that handles messages for the piece ofbuilding equipment.

The nodes of the graph can represent various devices or softwarecomponents. The edges can represent communication actions between thevarious devices or software components. For example, the edges couldrepresent API calls between the various software components. Referringto FIG. 12, API calls may exist for a device hub 1232 to implement acontrol command for a door actuator 1242. The API calls may be betweenother connecting software components, e.g., cluster 1236, connector A1240, connector B 1238, and external system 1244. To implement a controlcommand for door actuator 1242, the device hub 1232 may make an API call1284 to the cluster 1236 which may in turn make API calls 1286 and/or1288 to connectors A 1240 and connector B 1238. Connector A 1240 maymake an API call to external system 1244, API call 1288. Similarly,connector B 1238 may make an API call 1290 to external system 1244.External system 1244 may make an API call 1292 to the door actuator 1242to implement the requested command.

Similarly, if the command is to send an email via the email service1204, a connection broker 1254 may broker the connection for the cloudplatform 106 with the email service 1204 and may make one or more APIcalls to implement the email command. The connection broker 1254 maymake an API call 1298C to the cluster 1208 which may make an API call1298 d to a connector A that makes an API call 1298 f with the emailservice 1204 to send an email.

In step 1906, the cloud platform 106 causes the service identified instep 1904 to perform the operation based on the communication actionsrepresented by the edges. For example, the cloud platform 106 canidentify a set of API calls that implement the action. The API calls canbe identified in part based on the graph. For example, to implementsending an email, the cloud platform 106 can identify API call 1298 cmake by connection broker 1254, API call 1298 d made by cluster 1208,and API call 1298 f made by connector A 1206. The cloud platform 106 cancause each service (i.e., connection broker 1254, cluster 1208, andconnector A 1206) to make the appropriate API call to implement theaction.

Referring now to FIG. 20, a process 2000 where a user or service isprovided with information and control abilities based on policies storedwithin a graph that can be performed by the cloud platform 106 is shown,according to an exemplary embodiment. The cloud platform 106 can beconfigured to perform the process 2000. In some embodiments, anycomputing device or system described herein can be configured to performthe process 2000.

In step 2002, the cloud platform 106 receives a request to view aportion of a graph of nodes and edges from a user and/or service. Thenodes can represent entities of a building while the edges can representrelationships between the entities of the building. The request can bereceived from a user via the user device 176. The request can bereceived from the applications 110 and/or the building subsystems 122,in some embodiments.

In step 2004, the cloud platform 106 can determine whether the userand/or service has access to view the portion of the graph based on apolicy indicated by one or more nodes and/or relationships of the graph.For example, the graph can indicate a policy for viewing information ofthe graph. For example, referring to FIG. 11, an entity 1103 has 1151the policy 1136 to read events 1138 to the floor 1132. In this regard,if the user and/or service is the entity with a policy to read events,the user and/or service could view the events 110 and/or 1112.

The policy of the user and/or service could cascade through the graph,for example, if the user and/or service has a policy to read informationfor a higher level node, lower level nodes are also available to theuser and/or service. For example, the cloud platform 106 could identifythat the entity 1103 has 1151 the policy 1136 to the floor 1132 via edge1174. Because the door actuator 1114 is an asset of the space 1130indicated by the edge 1168 and that the space 1130 is a space of thefloor 1132 indicated by the edge 1170, the cloud platform 106 canidentify that the entity 1103 has access to the events of the dooractuator 1114.

In step 2006, the cloud platform 106 can provide a user and/or servicean indication of the portion of the graph in response to determiningthat the policy indicates that the user and/or service has access toview the portion of the graph. The cloud platform 106 can cause adisplay device of the user device 176 to display the indication of theportion of the graph in some embodiments. In step 2008, the cloudplatform 106 can receive a command for a piece of equipment. The commandmay be a command to operate the piece of equipment, in some embodiments.In some embodiments, the command is a command to perform an action onbehalf of a user, e.g., send an email to a user, schedule a meeting withthe user, etc.

In step 2010, the cloud platform 106 can determine whether the user orservice has access to perform the command based on a policy indicated byone or more nodes and/or edges of the graph. For example, a policy ofthe graph can indicate that the user and/or service has access tooperate the piece of equipment.

For example, referring to FIG. 12, the user bob 1220 has a send commandpolicy for a particular floor, e.g., Bob 1220 has 1264 policy 1136 forthe send command 1140 via the edge 1178. The policy 1136 is set for thefloor 1132 via the edge 1174. Because the entity 1103 has a send commandpolicy for the floor 1132, any piece of equipment on the floor can becommanded by the entity 1103. For example, the door actuator 1114 is apiece of equipment of a space 1130 indicated by edge 1168. The space1130 is a space of the floor 1132 indicated by the edge 1170. The dooractuator 1114 has a capability 1248 indicated by edge 1180, the commandcan be an open door command 1252 or a lock door command 1250 related tothe capabilities 1248 of the door actuator 1114 via the edges 1296 and1294.

The cloud platform 106 can determine that the user Bob 1220 has theability to command the door actuator 1114 via the relationships betweenthe door actuator 1114 and the floor 1132 that the policy 1136 is setfor. Because the user Bob 1220 has the ability to make commands for thefloor 1132, all components related to the floor 1132, e.g., are locatedon the floor 1132, can be available to the user, e.g., the door actuator1114 being a device of the space 1130 via the edge 1168 and the space1130 being an area of the floor 1132 via the edge 1170.

In step 2012, the cloud platform 106 can operate the piece of equipmentto perform the command. The cloud platform 106 can, in some embodiments,identify the services and/or communication actions to implement thecommand as described in FIG. 19. For example, the cloud platform 106 canutilize the graph to identify the services that handle messaging for thedevices and can identify the communication actions that the serviceperforms to implement the command.

Referring now to FIG. 21, a process 2100 where a graph projection isconstructed by the twin manager 108 is shown, according to an exemplaryembodiment. In some embodiments, the twin manager 108 is configured toperform the process 2100. In some embodiments, components of the twinmanager 108, e.g., the graph projection manager 156, is configured toperform the process 2100. In some embodiments, any computing devicedescribed herein is configured to perform the process 2100.

In step 2102, the twin manager 108 can receive a request for a graphprojection from a system. For example, a user via the user device 176may request a graph projection be generated. In some embodiments, thecloud platform 106 receives an indication of a new subscribing customerand the cloud platform 106 provides a request to the twin manager 108 togenerate a new projection for the subscribing customer. In someembodiments, the twin manager 108 receives a request from theapplications 110 for a graph projection to be generated for a specificapplication of the applications 110.

In step 2104, the twin manager 108 retrieves projection rules for thesystem for generating the graph projection. The projection rules can bean ontology specific for the system. For example, the ontology candefine what types of nodes can be related in what particular ways. Forexample, one ontology may indicate that one type of node (e.g.,thermostat) should be related to another type of node (e.g., a space).The ontology can indicate each type of node and what second types ofnodes that each type of node can be related to. Furthermore, theprojection rules can indicate policies for the system. For example, theprojection rules can identify what nodes and/or edges that the systemhas access to view.

In step 2106, the twin manager 108 can retrieve entities and/orrelationships representing entities of a building and relationshipsbetween the entities of the building. The twin manager 108 can retrieveall entities and/or relationships from the entity, relationship, andevent database 160. In some embodiments, the twin manager 108 retrievesonly the entities and/or relationships that the projection rulesindicate should be included within the projection graph, e.g., onlyentities and/or relationships that correspond to the ontology or onlyentities and/or relationships that the system has an access policy to.

In step 2108, the twin manager 108 can construct the graph projectionbased on the entities and relationships retrieved in the step 2106 andthe projection rules retrieved in the step 2104. In some embodiments,the twin manager 108 can construct the graph projection by generatingnodes for the entities and generating edges between the nodes torepresent the relationships between the entities.

In some embodiments, the twin manager 108 generates the graph projectionbased on the ontology. For example, the ontology may indicate thatbuilding nodes should have an edge to room nodes. Another ontology mayindicate that building nodes should have an edge to floor nodes andfloor nodes should have an edge to room nodes. Therefore, for entitydata that indicates a building A has a floor A and that floor A has aroom A, with the first ontology, a node for the building A can begenerated along with an edge from the building A node to a room A node.For the second ontology, a building A node with an edge to a floor Anode can be generated. Furthermore, the floor A node can have an edge toa room A node.

In step 2110, the building data platform 100 can perform one or moreoperations based on the graph projection. In some embodiments, thebuilding data platform 100 can perform event enrichment with contextualinformation of the graph projection (e.g., as described in FIG. 16). Insome embodiments, the building data platform 100 can generate a changefeed based on changes to the graph projection (e.g., as described inFIG. 17). In some embodiments, the building data platform 100 canutilize the graph projection to command and control entities representedby the graph projection (e.g., as described in FIG. 20). In someembodiments, the building data platform 100 can utilize the graphprojection to identify services and/or communication commands toimplementations (e.g., as described in FIG. 19).

Referring now to FIG. 22, a process 2200 where a graph is queried basedon an entity and an event is shown, according to an exemplaryembodiment. The cloud platform 106 can be configured to perform theprocess 2200. In some embodiments, any computing device described hereincan be configured to perform the process 2200.

In step 2202, the cloud platform 106 receives a query for information ofa graph, the query including an entity and an event. The query can beformed from parameters for an asset, point, place, location, and event(“APPLE”). The query can indicate an entity, one of an asset, point,place, and location while the query can further indicate an event. Inthis regard, the query can search for certain entities with a particularevent, for example, a floor (type of asset) with an active door alarm(event), a door (type of asset) with an active door alarm (event), abuilding (type of asset) with a temperature measurement exceeding aparticular amount (event), etc.

In step 2204, the cloud platform 106 queries the graph for informationbased on the query received in the step 2202 where the graph includesnodes and edges, the nodes representing entities and events and theedges representing relationships between the entities and the events.For example, the query can be run against the graph to identify anentity associated with a particular event.

For example, referring now to FIG. 11, if the query is to find a spacewith a door actuator value of 1 at a particular time, “a,” the cloudplatform 106 can be configured to search the edges and nodes to firstall spaces within the graph. Next, the cloud platform 106 can selectspaces of the graph that are linked to an event node for a door actuatorwith a value of 1 at a particular time, “a.” For example, the cloudplatform 106 can determine that the space 1130 has an edge 1168 to thedoor actuator 1114 and that the door actuator 1114 has an edge 1160 to apoint A 1116 and that the point A 1116 has an edge to the TS 1120 whichin turn has an edge 1168 to the event node 1110 which has a value of 1at a time “a.”

In step 2206, the cloud platform 106 can generate a query response basedon the information queried in the step 2204. The query response caninclude one or more nodes and/or edges of the graph selected by thequery. For example, the query response could identify the entity of thequery. Furthermore, the query response could identify the entity of thequery and one or more nodes and/or edges relating the entity to theevent of the query. The cloud platform 106 can return the query responseto a system that originally made the query, e.g., to the user device176, the applications 110, the building subsystems 122, etc.

Referring now to FIG. 23, the platform manager 128 of the cloud platform106 managing tenant and subscription entitlements with a tenantentitlement model 2300 is shown, according to an exemplary embodiment.The platform manager 128 can be configured to manage entitlements ofvarious tenants and/or tenant subscriptions for the building dataplatform 100. The provisioning service 130 can receive data from a userdevice 176 to create, end, or update a tenant and/or tenantsubscription. The provisioning service 130 can cause the subscriptionservice 132 to update the tenant entitlement model 2300 appropriately.

In some embodiments, the provisioning service 130 is configured tohandle license purchases and/or license activation for a tenant and/ortenant subscription. A user, via the user device 176, can purchase alicense for a particular tenant subscription through the provisioningservice 130. Responsive to the purchase of the license, the provisioningservice 130 can add the entitlement for the tenant subscription to thetenant entitlement model 2300, activating the license purchased.

The tenant entitlement model 2300 can indicate tenants, each tenantindicating a billing boundary. Each tenant can further include one ormultiple subscriptions, particular implementations of the building dataplatform 100 for the tenant. For example, a retail chain that includesmultiple stores could be a tenant while each store could have aparticular subscription. Each subscription can be tied to a particulargeographic operating zone, e.g., an indication of computing resourceswithin the geographic operating zone that the subscription utilizes.Each subscription can further indicate entitlements for thesubscription, e.g., services, data, or operations of the building dataplatform 100 that the subscription is authorized to utilize.

The entitlement service 134 can receive requests for entitlements fromsystems 2302 (e.g., the edge platform 102, the twin manager 108, and/orapplications 110). The request may be a question whether a particularsubscription has authorization for a particular entitlement, forexample, the question could be whether a particular subscription hasaccess to make a command responsive to systems 2302 requesting to makethe command. In some embodiments, while the systems 2302 are operating(e.g., processing a control command, enriching an event, generating auser interface, performing a control algorithm), they may encounter anaction that requires an entitlement. Responsive to encountering theaction requiring the entitlement, the systems 2302 can communicate withthe entitlement service 134 to determine whether the particularsubscription that the systems 2302 are performing the action for has anentitlement for the action.

The platform manager 128 includes a throttle manager 2304 configured toperform throttling operations for particular tenants and/or tenantsubscriptions. For example, a particular tenant may have an entitlementto make a certain number of commands per minute, receive a certainamount of event data from building systems a minute, utilize aparticular amount of processing power to run applications, etc. Thethrottle manager 2304 can receive operating data from the systems 2302,in some embodiments through a meter 2306 of the platform manager 128. Insome embodiments, the meter 2306 receives the operating data, analyzesthe operating data to determine metrics (e.g., commands per minute,storage utilized, etc.) for particular tenant subscriptions.

The throttle manager 2304 can communicate a resource throttling commandfor particular customer subscriptions to the systems 2302. For example,if a customer subscription has an entitlement for a particular number ofevent enrichment operations and the operating data indicates that theparticular number of event enrichment operations have been performed,the throttle manager 2304 can send a throttle command for eventenrichment (e.g., stop all enrichment for the tenant subscription, causethe enrichment to be slowed, etc.). In some embodiments, the throttlemanager 2303 could slow down operating commands of a particular tenantsubscription in response to receiving more than a particular number ofrequests to perform operating commands in a particular time period(e.g., 1,000 requests in a minute).

The meter 2306 can be configured to generate metrics indicating theoperations of the systems 2302 for the tenant subscriptions and/or forthe tenants. The meter 2306 can receive the operating data from thesystems 2302 and determine which tenant subscription the operating datais associated with. For example, the systems 2302 may record whichtenant subscription is associated with the operating data and provide anindication of the tenant subscription to the meter 2306. The operatingdata can be a control command, an amount of events received by thesystems 2302 from building systems of a building, etc. The metricsgenerated by the meter 2306 can indicate computational resources used byparticular tenant subscriptions, storage resources used by particulartenant subscriptions, number of computing request or commands made, etc.In some embodiments, the meter 2306 is configured to generate a bill forparticular tenants and/or tenant subscriptions based on the metrics toscale bills of tenant subscriptions based on their usage of the systems2302.

In some embodiments, the meter 2306 generates metrics for one ormultiple tenant subscriptions. The metrics can be API request persecond, day, month, and total amount of data transferred. The metricscan indicate number of messages processed and/or computational cyclesused. The metrics can indicate amount data storage used and/or amount ofdata persisted. The metrics can indicate events per second, per day,and/or per month. Furthermore, the metrics can indicate eventsubscriptions per second, per day, and/or per month. A tenant may haveone or multiple event subscriptions indicating how the data platform 100handles and/or enriches particular events.

Referring now to FIG. 24, the tenant entitlement model 2200 shown ingreater detail, according to an exemplary embodiment. In someembodiments, the tenant entitlement model 2200 is a graph datastructure, one or more tables, or other data storage structures. Thetenant can be a billing boundary. The tenants can have multiplesubscriptions, e.g., multiple sites of a single entity, multiple floorsof a building rented to various companies, etc. The tenant 2400 is shownto include three separate subscriptions, subscription A 2402,subscription B 2404, and subscription C 2406. The tenant 2400 can be aparticular account associated with a globally unique identifier (GUID)linked to particular subscription identifiers.

Each of the subscriptions 2402-2406 can be associated with a particulargeographic zone, e.g., zone 2408 and zone 2410. The zones can beparticular geographic regions such as cities, counties, states,countries, continents, country groupings (e.g., Asia Pacific (APAC),Europe, the Middle East and Africa (EMEA), etc.), etc. Each of thesubscriptions 2402-2406 can be linked to one of the zones 2408 and 2410.Each of the geographic zones 2408 and 2410 can be associated withcomputational resources (e.g., servers, processors, storage devices,memory, networking infrastructure, etc.) located within each of thezones for implementing the building data platform 100. The computationalresources within each zone can be shared amount subscriptions for thezone.

In some embodiments, the building data platform 100 can implement DNSstyle data routing to the computational resources of the zones based onsubscription identifiers for the subscriptions 2402-2406. The zones 2408and 2410 can resolve data residency concerns, e.g., that data of aparticular subscription does not leave a particular geographic district,e.g., leave a country.

Each of the zones 2408 and 2410 can indicate entitlements forsubscriptions linked to the zones 2408 and 2410. For example, a table2414 can indicate entitlements for the subscription A 2402 and thesubscription B 2404 linked to the zone 2408. A table 2412 can indicateentitlements for subscriptions of the zone 2410, e.g., the subscriptionC 2406. The tables 2414 and 2412 can indicate all entitlements offeredby the building data platform 100 for the particular zone and whethereach subscription has authorization for the particular entitlement. Theentitlements can indicate what services, resources, and/or whatcomputing, storage, and/or networking usage levels the subscriptions2402-2406 are entitled to.

For example, the building data platform 100 includes platform resources2413 and 2418 for the zones 2408 and 2410 respectively. In the zone2408, the platform resources 2413 include computing resources 2414 andstorage resources 2416. In the zone 2410, the platform resources 2418include computing resources 2420 and storage 2422. The building dataplatform 100 can facilitate resource scaling providing the subscriptionA 2402 and the subscription B 2404 various amounts of the platformresources 2413 according to entitlements for the subscription A 2402 andthe subscription B 2404 respectively. Each subscription can be assignedan amount of resource based on whether the subscription is assigned, viathe entitlements, a premium resource usage tier or a lower levelresource usage tier.

The entitlements can be a set of available capabilities within one ofthe zones 2408 and 2410 that the subscriptions 2402-2406 are assigned orare not assigned. The entitlements can be availability of the graph,events, commands, event subscriptions, gateway operations, and/orgateway cloud to device (C2D) communication. In some embodiments, theability to create an event subscription, e.g., an ER collection, graph,and/or enrichment rule for a particular event or type of events can beavailable to some subscriptions but not to others. The platform manager128 can provide an API, e.g., through the provisioning service 130, thesubscription service 132, and/or the entitlement service 134, formanaging the entitlements of the tenant entitlement model 2300.

Referring now to FIG. 25, a process 2500 of managing tenant andsubscription entitlements with the tenant entitlement model 2300 isshown, according to an exemplary embodiment. In some embodiments, theplatform manager 128 is configured to perform the process 2500. Anycomputing device or system described herein can be configured to performthe process 2500, in some embodiments.

In step 2502, the platform manager 128 is configured to receive one ormore tenant and/or subscription management requests from the user device176. For example, the requests can be to create a new tenant and/or newsubscription for a tenant, remove an existing tenant and/or existingsubscription, update entitlements for subscriptions, etc. In someembodiments, the requests are associated with purchases, e.g.,purchasing an entitlement for a particular subscription. In someembodiments, the request can indicate management of subscription zonerelationships, e.g., a management of what zone an existing or newsubscription is set for. In some embodiments, the entitlements set forthe subscription are limited to the entitlements available for aparticular zone that the subscription is linked to. In step 2504, theplatform manager 128 can update the tenant entitlement model 2300 basedon the request received in the step 2502.

In step 2506, the platform manager 128 receives a request to perform anoperation for a subscription for a zone from one of the systems 2302.For example, one of the systems 2302 can provide the request to theplatform manager 128 to determine whether an operation is available fora subscription. For example, the twin manager 108 may process a commandrequest to command a particular piece of equipment of the buildingsubsystems 122 for a particular subscription. The twin manager 108 cansend a request to the platform manager 128 for confirmation of whetherthe subscription has_a command entitlement for a particular zone.

In response to receiving the request of the step 2508, the platformmanager 128 can determine whether the subscription has the entitlementfor the operation for the zone based on the tenant entitlement model2200. For example, the platform manager 128 can search entitlements forthe particular zone that the subscription is linked to in order todetermine whether the subscription has the entitlement for theoperation. The platform manager 128 can respond to the system with anindication of whether or not the subscription has the entitlement.

In step 2510, the building data platform 100 can implement the operationwith computing resources for the zone linked to the subscription by thetenant entitlement model. For example, the platform manager 128 canrespond to the system where the system is a component of the buildingdata platform 100 with an indication that the subscription has theentitlement. The system can proceed with performing the operation.Furthermore, the subscription may be tied to a zone which is linked tocomputing resources of the building data platform 100. The operation canbe performed on the computing resources tied to the zone.

In step 2512, the platform manager 128 can perform metering and/orthrottling for the subscription based on the operation and/or one ormore additional operations. The platform manager 128 can track alloperational data associated with the subscription and build operationmetrics via the meter 2306. The metrics can indicate resource usage ofthe subscription. Based on the metrics, the platform manager 128 cangenerate bills based on the metrics to charge the subscription an amountaccording to the resource usage. Furthermore, based on the metrics theplatform manager 128 can implement resource throttling to control theamount of computing and/or storage resources used by the subscription.

Referring now to FIG. 26, a system 2600 including the edge platform 100performing event enrichment at the edge platform 102 before the eventsare communicated to the cloud platform 106 is shown, according to anexemplary embodiment. The system 2600 includes the building subsystems122, the edge platform 102, the cloud platform 106, the applications110, and the twin manager 108. The edge platform 102 can receive eventsfrom the building subsystems 122 and enrich the events before passingthe events on to the cloud platform 106. Because the edge platform 102is located on-premises, e.g., on the edge, the events can be enrichedbefore being passed on to other cloud systems and/or used in edge basedanalytics run on the edge platform 102. In some embodiments, processors,memory devices, and/or networking devices of the edge platform 102 arelocated on-premises within a building.

The edge platform 102 can receive events from the building subsystems122. The events can be data packages describing an event that hasoccurred with a timestamp of when the event occurred. The events can beraw events that are composed of content that is emitted from a producingsystem. However, the event may not include any intent or knowledge ofthe system that consumes it. The event can be of a particular eventtype. An enrichment manager 2602 of the edge platform 102 can receivethe events from the building subsystems 122. The enrichment manager 2602can be the same as, or similar to, the enrichment manager 138.

The enrichment manager 2602 can enrich the events received from thebuilding subsystems 122 based on event context received and/or retrievedfrom a lite digital twin 2608 of the edge platform 102. For example, theenrichment manager 2602 can add entity and/or entity relationshipinformation associated with the event to the event to generate theenriched events 2604. The event enrichment can be the same as or similarto the enrichment described with referenced to FIGS. 1-3 and FIG. 8. Theenriched events 2604 can be an event with additional added properties orattributes that provide context regarding the event.

In some embodiments, the enrichment manager 2602 includes multiple eventstreams. The event streams can be data enrichment processing streams forparticular events and/or particular types of events. Each event streamcan be linked to a tenant and/or tenant subscription. Each event streamcan indicate one or more rules for enriching an event, e.g., anindication of the information to add to the event. In this regard, oneevent can be applied to multiple event streams and receive differentenrichments to generate multiple enriched events. Each enriched eventcan be provided to a different application or end system.

The edge platform 102 includes edge applications 2610. The edgeapplications 2610 can be similar to or the same as the applications 110.While the applications 110 may be run on a cloud system, the edgeapplications 2610 can be run locally on the edge platform 102. The edgeapplications 2610 can operate based on the enriched events 2604 and maynot need to consult a digital twin to acquire context regarding an eventsince the enriched events 2604 may already include the needed context.In some embodiments, the edge application 2610 perform analytics (e.g.,aggregation, data monitoring, etc.), control algorithms, etc. for thebuilding subsystems 122.

For example the edge applications 2610 can generate control decisionsfor the building subsystems 122 based on the enriched events 2604, e.g.,temperature setpoints for zones, fan speed settings for fans, ductpressure setpoints, ventilation commands, etc. In some embodiments, theedge applications 2610 include models, e.g., machine learning models forpredicting characteristics and/or conditions and/or for operating thebuilding subsystems 122. In some embodiments, the machine learning isperformed at the edge platform 102 which results in higher scores thanmachine learning performed in the cloud since a greater amount of datacan be collected faster and used for training at the edge.

In some embodiments, the enrichment manager 2602 only operates when thetwin manager 108 is not operating and enriching events. For example, theedge platform 102 can receive an indication that there is an error withcloud systems, e.g., network issues, computing issues, etc. In thisregard, the edge platform 102 can take over enriching the events withthe enrichment manager 2602 and operating on the events with the edgeapplications 2610. In this regard, the enrichment and applicationoperation can dynamically move between the edge platform 102 and thecloud. Furthermore, load balancing can be implemented so that someevents are enriched and operated on by edge applications 2610 whileother events are passed to the cloud platform 106 and/or the twinmanager 108 for enrichment and provided to the applications 110 foroperation.

In some embodiments, by performing enrichment at the edge platform 102,analytics can be performed at the edge platform 102 based on theenriched events. In this regard, lower latencies can be realized sinceanalytics and/or control algorithms can be performed quickly at the edgeplatform 102 and data does not need to be communicated to the cloud. Insome embodiments, the edge applications 2610 and/or machine learningmodels of the edge applications 2610 can be built in the cloud andcommunicated to the edge platform 102 and additional learning can beperformed at the edge platform 102.

The edge platform 102 includes the lite digital twin 2608. The litedigital twin 2608 can be a version of a digital twin 2610 of the twinmanager 108. The digital twins 2610 and/or 2608 can be virtualrepresentations of a building and/or the building subsystem 122 of thebuilding. The digital twin 2610 and/or the digital twin 2608 can be orcan include the graph projection database 162, e.g., one or more graphdata structures. The digital twin 2610 and/or the lite digital twin 2608can be the graphs shown in FIGS. 11-13. In some embodiments, the litedigital twin 2608 is a projection that does not include all nodes andedges of a full projection graph. The lite digital twin 2608 may onlyinclude the nodes or edges necessary for enriching the events and can bebuilt on projection rules that define the information needed that willbe used to enrich the events.

In some embodiments, the lite digital twin 2608 can be synchronized, inwhole or in part, with the digital twin 2610. The lite digital twin 2608can include less information than the digital twin 2610, e.g., lessnodes or edges. The lite digital twin 2608 may only include the nodesand/or edges necessary for enriching events of the building subsystems122. In some embodiments, changes or updates to the digital twin 2610can be synchronized to the lite digital twin 2608 through a change feedof change feed events. The change feed can indicate additions, removals,and/or reconfigurations of nodes or edges to the graph projectiondatabase 162. Each change feed event can indicate one update to thedigital twin 2610.

A digital twin updater 2606 can receive the events of the change feedfrom the change feed generator 152 and update the lite digital twin 2608based on each change feed event. The updates made to the lite digitaltwin 2608 can be the same updates as indicated by the events of thechange feed. In some embodiments, the digital twin updater 2606 canupdate the lite digital twin 2608 to only include the nodes and edgesnecessary for enrichment of the events, and thus include less nodes andedges than the digital twin 2610.

In some embodiments, the digital twin updater 2606 filters out changefeed events if the change feed events do not pertain to informationneeded to enrich the events. In this regard, the digital twin updater2606 can store a list of information needed for enrichment, e.g., thedigital twin updater 2606 can include all event subscriptions orenrichment rules. The digital twin updater 2606 can determine whether achange feed event updates information pertaining to event enrichment andonly update the lite digital twin 2608 responsive to determining thatthe change feed event updates information needed for enrichment. In someembodiments, when a new event subscription and/or new enrichment rule iscreated, the digital twin updater 2606 can communicate with the digitaltwin 2610 to retrieve noes or edges needed for the new eventsubscription and/or enrichment rules.

Referring now to FIG. 27, a process 2700 of performing event enrichmentat the edge by the edge platform 102 before the events are communicatedto the cloud is shown, according to an exemplary embodiment. In someembodiments, the edge platform 102 is configured to perform the process2700. Furthermore, any computing system or device as described hereincan be configured to perform the process 2700.

In step 2702, the twin manager 108 can receive a change to the digitaltwin 2610 managed by the twin manager 108. The change can be anaddition, removal, or reconfiguration of an edge and/or node. In step2704, the twin manager 108 can update the digital twin 2610 based on thechange. Furthermore, in step 2706, the twin manager 108 can generate achange feed event for a change feed representing the change to thedigital twin. In some embodiments, the change feed event can summarizethe change. In step 2708, the twin manager 108 can communicate thechange feed to the edge platform 102 for synchronizing the digital twin2610 with the lite digital twin 2608 of the edge platform 102.

In step 2710, the edge platform 102 can receive the change feed from thetwin manager 108. The edge platform 102 can be subscribed to the changefeed and can receive all change feed events posed to the change feed bythe twin manager 108. In step 2712, the edge platform 102 can update thelite digital twin 2608 based on the change feed event. In someembodiments, the edge platform 102 can determine, responsive toreceiving the change feed event, whether the change feed event affectsenrichment performed by the edge platform 102. Responsive to determiningthat the change feed event affects nodes or edges of the lite digitaltwin 2608 used in enrichment, the edge platform 102 can update the litedigital twin 2608 based on the change feed event.

In step 2714, the edge platform 102 can receive one or more events frombuilding systems of a building. For example, the building subsystems 122can generate events, e.g., data collection events, operational commanddecisions, etc. The events can describe information created for thebuilding subsystems 122 and include a timestamp indicating when theinformation was created.

In step 2716, the edge platform 102 can retrieve event context from thelite digital twin 2608 for the one or more events. The event context canindicate attributes describing the event. In step 2718, the edgeplatform 102 can generate the enriched events 2604 by enriching the oneor more events with the event context retrieved in the step 2718.Enriching the events can include adding additional attributes (the eventcontext) to the events. In step 2720, the edge platform can communicatethe one or more enriched events 2604 to the cloud, e.g., the cloudplatform 106.

Referring now to FIG. 28, a system 2800 including the twin manager 108synchronizing the digital twin 2610 of the twin manager 108 with digitaltwins of other external systems is shown, according to an exemplaryembodiment. The twin manager 108 can act as a master record of a digitaltwin of a building and/or building subsystems and use a change feed toupdate digital twins of other systems, e.g., an external system 2806 and2816. Furthermore, in some embodiments, the twin manager 108 can receiveupdates to the digital twin of one external system, e.g., the externalsystem 2806 and synchronize the changes to other external systems, e.g.,the external system 2816. This synchronization can allow for datasharing between all of the digital twins since each digital twin isup-to-date.

The twin manager 108 includes the digital twin 2619 and the change feegenerator 152. Furthermore, the twin manager 108 includes a twin updater2802 and a change synchronizer 2804. The twin updater 2802 can receiveupdates to the graph projection database 162, e.g., updates to nodes oredges of the graph, e.g., insertion, deletion, or reconfiguration ofnodes or edges. The updates can be received from the cloud platform 106as part of the event processing shown in FIG. 3 where updates to thegraph are learned from events. In some embodiments, the updates canoriginate from other systems, e.g., the external system 2806 or 2816.For example, the external system 2806 could make an update to a digitaltwin 2808 in a first format stored by the external system 2806 andcommunicate the change to the twin updater 2802. In some embodiments,the external system 2806 can use a change feed to communicate the updateto the twin manager 108.

The change synchronizer 2804 can synchronize the digital twin 2610 withthe digital twin 2808 of the external system 2806 and a digital twin2814 of the external system 2816. The change synchronizer 2804 can makeupdates to the digital twin 2808 and the digital twin 2814. In someembodiments, the change synchronizer 2804 makes different types ofupdates based on the format of the digital twins 2808 and 2814. Forexample, the change synchronizer 2804 can make a twin update in a firstformat for the digital twin 2808 and a twin update in a second formatfor the digital twin 2814 to make the same update across the twins 2808and 2814.

In some embodiments, the change synchronizer 2804 uses a change feed ofchange feed events to update the digital twin 2808 and the digital twin2814. In some embodiments, the change synchronizer 2804 receives achange feed of change feed events from the change feed generator 152.Responsive to receiving a new change feed event, the change synchronizer2804 can make the change indicated by the change feed event in thedigital twin 2808 and the digital twin 2814. In some embodiments, thechange synchronizer 2804 communicates the change feed to the externalsystem 2806 and/or the external system 2814 causing the external system2806 and the external system 2816 to update the digital twins 2808 and2814.

The external system 2806 can receive updates from the changesynchronizer 2804 and update the digital twin 2808 according to theupdates. Similarly, a twin updater 2812 of the external system 1816 canreceive updates from the change synchronizer 2804 and update the digitaltwin 2814. In some embodiments, the updates received from the changesynchronizer 2804 are in a format associated with the digital twinstored by the external systems 2806 and/or 2816. In some embodiments,the update is a change feed event and/or a change feed of change feedevents.

In some embodiments, the building data platform 100 can generate litegraph projection of the digital twin 2610 and the digital twin in thefirst format 2808 and the digital twin in the second format 2814. Theprojections can be built based on projection rules and therefore may notinclude all of the nodes and edges as a full graph projection. The sameprojection rules can be used for the twin manager 108 and the externalsystem 2806 and/or the external system 2816. The building data platform100 can compare the projections against each other to confirm that thetwins of the twin manager 108 and the external system 2806 and/or 2816are the same. By comparing the projections instead of the full twins, aneasier feasible comparison can be performed.

Referring now to FIG. 29, a process 2900 of synchronizing the digitaltwin 2610 of the twin manager 108 with digital twins 2808 and 2814 ofother external systems 2806 and 2816 is shown, according to an exemplaryembodiment. In some embodiments, the twin manager 108 is configured toperform the process 2900. Any computing device or system describedherein can be configured to perform the process 2900, in someembodiments.

In step 2902, the twin manager 108 receives an update to the digitaltwin 2610. The update can be received from an internal system, e.g., acomponent of the building data platform 100. For example, eventsprocessed by the cloud platform 106 can be analyzed to derive updates tothe digital twin 2610 as described in FIG. 3. Similarly, in someembodiments, a user via the user device 176 can provide the update tothe digital twin 2610 to the twin manager 108. In some embodiments, anexternal system can provide the update, e.g., the external system 2806and/or the external system 2816. In this regard, the external system2806 can make an update to the digital twin 2808 and communicate theupdate made to the digital twin 2808 to the twin manager 108.

In step 2904, the twin manager 108 updates the digital twin 2610 basedon the update received in the step 2902. In step 2906, the twin manager108 generates a change feed event of a change feed based on the update.The change feed event represents the changes made to the digital twin2610. In some embodiments, the change feed is a topic where multiplechange feed events are posted for consuming systems to receive.

In step 2908, the twin manager 108 generates a first update in a firstformat for the digital twin 2808 based on the change feed event.Furthermore, the twin manager 108 generates a second update in a secondformat for the digital twin 2814 based on the change feed event. In step2910, the twin manager 108 can synchronize the digital twin 2808 of theexternal system 2806 with the update in the first format bycommunicating with the external system 2806. In step 2912, the twinmanager 108 can synchronize the digital twin 2814 of the external system2816 with the update in the second format by communicating with theexternal system 2816.

Referring now to FIG. 30, a system 3000 including an enrichment loop isshown, according to an exemplary embodiment. The system 3000 can includeevent sources 3005, 3010, and/or 3015. The event source 3005 can providean event 3020 to the enrichment manager 138. The event source 3010 canprovide an event 3025 to the enrichment manager 138. The event source3015 can provide an event 3030 to the enrichment manager 138. In someembodiments, the event sources 3005, 3010 and/or 3015 can be a buildingdata source of a building and/or a data source that is external to thebuilding. For example, the event sources 3005, 3010 and/or 3015 can beat least one of a temperature sensor, a motion sensor, a camera, an HVACdevice, a fire detection device, a badge scanner, a light, a door locksystem or any device described herein. In some embodiments, the datasource can be a digital twin of the building. The digital twin can be orinclude a building graph that provides a contextual or virtualdescription of a building and the various entities of the building. Insome embodiments, various data discussed herein may be stored in,retrieved from, or processed in the context of digital twins. In somesuch embodiments, the digital twins may be provided within aninfrastructure such as those described in U.S. patent application Ser.No. 17/134,661 filed Dec. 28, 2020, 63/289,499 filed Dec. 14, 2021, andSer. No. 17/537,046 filed Nov. 29, 2021, the entireties of each of whichare incorporated herein by reference. A digital twin can be a virtualrepresentation of a building and/or an entity of the building (e.g.,space, piece of equipment, occupant, etc.). A virtual representation ofa building could be a graph data structure. The virtual representationcould be a graphic model, e.g., a building information model (BIM). Thevirtual representation of the building could be a hierarchical model, insome embodiments. Furthermore, the digital twin can represent a serviceperformed in a building, e.g., facility management, equipmentmaintenance, etc.

Additionally, the event sources 3005, 3010 and/or 3015 can be anexternal source. For example, a system that produces a social mediafeeds, a system that produces a weather feed, a system that produces anew feeds, a system that produces a government emergency feed, data fromother buildings, calendar systems, smartphones, human resource (HR)systems, meeting scheduling systems, transit systems. The events 3020,3025 and/or 3030 can be generated in response to the event sources 3005,3010 and/or 3015 performing an operation, measuring a value, receiving atrigger, receiving a command, detecting a change of value, identifying atimer expiring. For example, the events 3020, 3025 and/or 3030 can bethe temperature sensor detecting a temperature, a badge scannerdetecting a badge, a thermostat receiving a new setpoint from a user.Additionally, the events 3020, 3025 and/or 3030 can be a weatherforecast produced by a weather system, a transit schedule for a trainsystem, news events received from a news feed.

The enrichment manager 138 can identify additional information that isassociated with the events 3020, 3025 and/or 3030. In some embodiments,the additional information can be contextual data. The contextual datacan provide a context for the events 3020, 3025 and/or 3030. Forexample, the contextual data can indicate a location of the eventsources 3005, 3010, and/or 3015. For example, the contextual data canindicate a location of a camera. The location of the event sources canalso identify a campus, building, a floor, a zone room, or wall that theevent source is located. For example, the contextual data can indicatethat the event source 3005 is located at zone 1, zone 1 is located onfloor 2 and zone 1 and floor 2 are located within building A. In someembodiments, the contextual data is an indication of information relatedto the events 3035, 3040, and/or 3045. For example, if the event 3025 isa timeseries temperature measurement of a thermostat, the contextualdata can include the location of the thermostat (e.g., what room), theequipment controlled by the thermostat (e.g., what VAV), etc.

In some embodiments, the enrichment manager 138 can identify thecontextual data that pertains to events 3020, 3025 and/or 3030 byquerying one or more graphs. For example, the enrichment manager 138 canidentify contextual data by querying the graphs depicted in FIGS. 11-13and/or 32. In some embodiments, the enrichment manager 138 can identifythe contextual data by performing similar steps to that describe inprocess 2200. In some embodiments, the enrichment manager 138 canproduce one or more enriched events 3035, 3040 and/or 3045 by combiningthe contextual data and the events 3020, 3025 and/or 3030. For example,the enrichment manager 138 can identify a node in the graph representingthe event source. The enrichment manager 138 can traverse the edgesconnected to the node to other nodes. The other nodes can provide thecontextual description of the event. The enrichment manager 138 canretrieve the other nodes and use the other nodes as contextual data toenrich the events 3020, 3025, and/or 3030.

In some embodiments, the enrichment manager 138 can generate theenriched event 3035 by combining the event 3020 and the contextual datathat pertains to the event 3025. In some embodiments, the enriched event3040 can be generated by the enrichment manager 138 by combining theevent 3025 and the contextual data that pertains to the event 3025 intothe enriched event 3040. In some embodiments, the enriched event 3045can be generated by combining the event 3030 and the contextual datathat pertains to the event 3030. In some embodiments, the enrichmentmanager 138 can generate the enriched event 3035 by combining the events3020, 3025 and/or 3030. In some embodiments, the enrichment manager 138can generate the enriched event 3035 by combining the events 3020, 3025and the contextual data that pertains to the event 3020 and/or the event3025. In some embodiments, the enrichment manager 138 can determine thatthe contextual data that pertains to the event 3025 also pertains to theevent 3020. In some embodiments, the enrichment manager 138 can generatethe enriched event 3035 by combining the event 3020 and the contextualdata that pertains to the event 3025.

In some embodiments, the enrichment manager 138 can generate theenriched event 3040 by modifying the event 3025 and/or the contextualdata that pertains to the event 3025. In some embodiments, theenrichment manager 138 can generate the enriched event 3040 by combiningthe modified event 3025 and the contextual data that pertains to themodified event 3025.

In some embodiments, the enrichment manager 138 can modify the events3020, 3025 and/or 3030 by deleting one or more of the events 3020, 3025and/or 3030. In some embodiments, the enrichment manager 138 candetermine that the event 3020 and the event 3025 are conflicting events.In some embodiments, the events 3020 and 3025 can be conflicting eventswhen the events 3020 and 3025 both pertain to the same piece of buildingequipment but the events 3020 and 3025 have a different value. Forexample, the events 3020 and 3025 are both ventilation rates for thesame HVAC device. However, the ventilation rate for the event 3020 isdifferent from the ventilation rate for the event 3025. In someembodiments, the enrichment manager 138 can use the contextual data toresolve the conflict. For example, the contextual data that pertains tothe events 3020 and 3025 can include information pertaining to themaintenance schedule of the HVAC device. In some embodiments, theenrichment manager 138 can determine, using the maintenance schedule,that the event 3020 is a faulty event (e.g., the event occurred whileHVAC device was undergoing maintenance). In some embodiments, theenrichment manager 138, upon determining that the event 3020 is a faultevent, can delete the event 3020.

In some embodiments, the enrichment manager 138 can modify the events3020, 3025 and/or 3030 by combining one or more of the events 3020, 3025and/or 3030. In some embodiments, the enrichment manager 138 candetermine that the events 3020 and 3025 are the same event (e.g., theenrichment manager 138 received the same event more than once). In someembodiments, the enrichment manager 138 can use the contextual data thatpertains to the events 3020 and 3025 to determine that the events 3020and 3025 are the same. For example, the enrichment manager 138 candetermine that the contextual data that pertains to the event 3020matches the contextual data that pertains to the event 3025. In someembodiments, the enrichment manager 138, upon determining that thecontextual data matches, can determine that the events 3020 and 3025 arethe same. In some embodiments, the enrichment manager 138 can combinethe events 3020 and 3025 to generate a new event. In some embodiments,the enrichment manager 138 can generate the enriched events 3035, 3040and/or 3045 by combining the events 3020 and 3025 to generate the newevent and then combining the new event with the contextual data thatpertains to the events 3020 and 3025.

In some embodiments, the enrichment manager 138 can interface with asubscription database 3085. The subscription database 3085 can store oneor more subscriptions and one or more events that are linked to thesubscriptions. In some embodiments, the subscriptions can besubscriptions 3050, 3055 and/or 3060. In some embodiments, the eventscan be the events 3020, 3025, 3030 and/or the enriched events 3035, 3040and/or 3045. In some embodiments, the enrichment manager 138 cangenerate the subscriptions 3050, 3055 and/or 3060. For example, theenrichment manager 138 can receive a request from a consuming system3065 and/or an artificial intelligence (AI) model 3070. The consumingsystem 3065 can be or include an AI model, a machine learning (ML)model, an application, a rules engine, a device, a system, an internalcomponent of the data platform 100, an external component of the dataplatform 100. The consuming system 3065 can be or include the AI model3070. The AI model 3070 can be a model or application that implementsartificial intelligence. The AI model 3070 can include machine learning.The AI model 3070 can include supervised or unsupervised machinelearning. The machine learning can include neural networks, e.g.,sequence to sequence neural networks, recurrent neural networks,long-short term memory neural networks, convolutional neural networks, agradient boosting neural network, or any other type of neural network.The machine learning can include decision trees, Bayesian networks,hierarchical Bayesian networks, etc.

The request can include one or more events that the consuming system3065 and/or the AI model 3070 request to receive. In some embodiments,the enrichment manager 138 can interface with the subscription database3085 and determine whether a subscription exists that pertains to thisrequest. In some embodiments, the enrichment manager 138 can determinethat a subscription exists (e.g., subscription 3050). The enrichmentmanager 138, upon determining that the subscription 3050 exists, canenroll the consuming system 3065 and/or the AI model 3070 in thesubscription 3050. In some embodiments, enrolling the consuming system3065 and/or the AI model 3070 involves paring the consuming system 3065and/or the AI model 3070 to the subscription 3050. For example, when theconsuming system 3065 is enrolled in the subscription 3050 each time theenrichment manager 138 receives an event that is linked to thesubscription 3050 the enrichment manager 138 can provide the event tothe consuming system 3065.

In some embodiments, the enrichment manager 138, upon receiving arequest from the consuming system 3065 and/or the AI model 3070, candetermine that a subscription has not been generated (e.g., thesubscription does not exist). In some embodiments, upon determining thatthe subscription does not exist the enrichment manager 138 can generatea subscription, using the request received from the consuming system3065 and/or the AI model 3070.

In some embodiments, the subscriptions 3050, 3055 and/or 3055 can definecategories, types, or requirements for one or more events that can beprovided to the consuming system 3065 and/or the AI models 3070. In someembodiments, the consuming system 3065 can be at least one of anapplication that is internal to a building system, a system that isseparate from a building system, a piece of code, a module and/or acontroller. For example, the consuming system 3065 can be theapplications 110 and/or the edge applications 2610 described herein. Insome embodiments, the AI models 3070 can be the machine learning modelsdescribed herein. In some embodiments, the AI models 3070 can be a modelthat is generated using artificial intelligence and/or machine learning.For example, the AI model 3070 can be a model generated using supervisedmachine learning, unsupervised machine learning, neural networks,Bayesian networks and/or decision trees. In some embodiments, the AImodel 3070 can make occupancy predictions, building load predictions,inferring ideal temperature setpoints, energy predictions and orequipment predictions.

The consuming system 3065 can be enrolled in the subscription 3050. Theconsuming system 3065 can receive the enriched event 3035 in response tothe subscription 3050 receiving the enriched event 3035 from theenrichment manager 138. In some embodiments, a consuming system can beenrolled in one or more subscriptions. For example, the consuming system3065 can be enrolled in subscriptions 3050 and 3055.

In some embodiments, the consuming system 3065 can produce one or moreconsuming system events 3080. In some embodiments, the consuming systemevents 3080 can be an action that was taken by the consuming system3065. In some embodiments, the consuming system 3065 can, responsive toreceiving an event that pertains to a subscription that the consumingsystem 3065 is enrolled in, generate the consuming system event 3080.For example, the consuming system 3065 can, based on the consumingsystem 3065 being enrolled in the subscription 3050, generate theconsuming system event 3080 responsive to receiving the enriched event3035. In some embodiments the consuming system events 3080 can occur inresponse to the consuming system 3065 receiving one or more eventsand/or one or more enriched events. Additionally, the consuming system3065 can generate the consuming system events 3080 prior to receivingone or more events and/or one or more enriched events. For example, theconsuming system events 3080 can be the consuming system 3065 adjustingthe ventilation rate of a HVAC device. The consuming system events 3080can be provided to the enrichment manager 138. The enrichment manager138 can use the consuming system events 3080 to enrich one or moreevents. In some embodiments, the enrichment manager 138 can use theconsuming system event 3080 to enrich the events 3020, 3025 and/or 3030.In some embodiments, the enrichment manager 138 can use the consumingsystem event 3080 to enrich an event that is produced by one or moreadditional consuming systems 3065. In some embodiments, the enrichmentmanager 138 can use the consuming system event 3080 to enrich the AIdecision 3075. In some embodiments, the enrichment manager 138 canidentify additional information that is associated with the consumingsystem events 3080. For example, the additional information can becontextual data that pertains to the consuming system events 3080. Insome embodiments, the enrichment manager 138 can identify the contextualdata that pertains to the consuming system events 3080 by querying abuilding graph. For example, the enrichment manager 138 can query thegraphs depicted in FIGS. 11-13 and/or 32 to identify the contextual datathat pertains to the events 3020, 3025, 3025 and/or the consuming systemevent 3080. In some embodiments, the enrichment manager 138 can generatethe enriched event 3035 by combining the consuming system event 3080 andthe contextual data that pertains to the consuming system event 3080. Insome embodiments, generating the enriched event 3035 using the consumingsystem event 3080 and the contextual data that pertains to the consumingsystem event 3080 can be referred to as an enrichment loop.

In some embodiments, the AI model 3070 can produce one or more AIdecisions 3075. In some embodiments, the AI decisions 3075 can occur inresponse to the AI model 3070 receiving one or more events and/or one ormore enriched events. In some embodiments, the AI model 3070 can,responsive to receiving an event that pertains to a subscription thatthe AI model 3070 is enrolled in, generate the AI decision 3075. Forexample, the AI model 3070 can, based on the AI model 3070 beingenrolled in the subscription 3060, generate the AI decision 3075responsive to receiving the enriched event 3045. Additionally, the AIModel 3070 can generate the AI decisions 3075 prior to receiving the oneor more events and/or the one or more enriched events. In someembodiments, the AI decisions 3075 can be a prediction that wasgenerated by a model. For example, an occupancy model can make aprediction associated with occupancy. The AI decisions 3075 can beprovided to the enrichment manager 138. The enrichment manager 138 canuse the AI decisions 3075 to enrich one or more events that can beprovided by the event sources 3005, 3010 and/or 3015. In someembodiments, the enrichment manager 138 can use the AI decision 3075 toenrich the events 3020, 3025 and/or 3030. In some embodiments, theenrichment manager 138 can use the AI decision 3075 to enrich an eventthat is produced by one or more additional AI models 3070. In someembodiments, the enrichment manager 138 can use the AI decisions 3075 toenrich the consuming system event 3080. In some embodiments, theenrichment manager 138 can identify additional information that isassociated with the AI decisions 3075. In some embodiments, theadditional information can be contextual data that pertains to the AIdecisions 3075. In some embodiments, the enrichment manager 138 canidentify the contextual data that pertains to the AI decisions 3075 byquerying a building graph. For example, the enrichment manager 138 canquery the graphs depicted in FIGS. 11-13 and/or 32. The enrichmentmanger 138 can use the additional information to enrich the AI decisions3075. In some embodiments, the enrichment manager 138 can generate theenriched event 3040 by combining the AI decision 3075 and the contextualdata that pertains to the AI decision 3075. In some embodiments,generating the enriched event 3040 using the AI decision 3075 and thecontextual data that pertains to the AI decision 3075 can be referred toas an enrichment loop.

In some embodiments, a consuming system can be enrolled in asubscription that allows the consuming system to ignore one or moreenriched events. For example, the consuming system 3065 can be enrolledin the subscription 3055. In some embodiments, the subscription 3055includes the enriched event 3040. In some embodiments, the consumingsystem 3065 can receive enriched events 3035, 3040 and 3045. Theconsuming system 3065, given that the consuming system 3065 is enrolledin the subscription 3055 and based on the enriched events 3035 and 3045being excluded from the subscription 3055, can ignore the enrichedevents 3035 and 3045.

In some embodiments, the enrichment loop does not implement machinelearning. Events received from an event source can be enriched by theenrichment manager 138. The enriched events can be pushed to a consumingsystem. The consuming system can publish its own events into the digitaltwin based on the enriched events. The published events can be enrichedand forwarded to another consuming system. This consuming system canreact to the events, for example, generate alerts, change setpoints ondevices, etc.

In some embodiments, the enrichment loop can include at least onemachine learning model and/or at least one consuming system. Events thatare received from an event source can be enriched by the enrichmentmanager 138. The enriched events can be pushed to a machine learningmodel. The machine learning model can publish events (e.g., inferences)into the digital twin based on the enriched events. The published eventscan be enriched and forwarded to a consuming system. The consumingsystem can react to the events, for example, generate alerts, changesetpoints on devices, etc. In some embodiments, the consuming system canbe at least one of an application, a rule engine, a device, an AI model,a component and/or a server.

In some embodiments, the enrichment loop can include one or more machinelearning models. Events that are received from an event source can beenriched by the enrichment manager 138. The enriched events can bepushed to a machine learning model. The machine learning model canpublish events (e.g., inferences) into the digital twin based on theenriched events. The published events can be enriched and forwarded toanother machine learning model. This machine learning model can use theevents as inputs to generate its own events (e.g. its own inferences)and can publish the events into the digital twin.

In some embodiments, the enrichment loop can include at least oneconsuming system and/or at least one machine learning model. Events thatare received from an event source can be enriched by the enrichmentmanager 138. The enriched events can be pushed to a consuming system.The consuming system can publish its own events into the digital twinbased on the enriched events. The published events can be enriched andforwarded to a machine learning model. The machine learning model, basedon the events, can publish events (e.g., inferences) into the digitaltwin.

Referring now to FIG. 31, a system 3100 is shown, according to anexemplary embodiment. The system 3100 can include the enrichment manager138, an occupancy model 3110, a digital twin manager 3120, an energymodel 3125 and an equipment model 3130. In some embodiments theoccupancy model 3110, the energy model 3125 and/or the equipment model3130 can be one of the consuming systems 3065 and/or one of the AImodels 3070. In some embodiments, the enrichment manager 138 can providean enriched occupancy event 3105 to the occupancy model 3110. Theenriched occupancy event 3105 can be an event that has been enriched bythe enrichment manager 138. In some embodiments, the enriched occupancyevent 3105 can be one of the enriched events 3035, 3040 and/or 3045. Theenriched occupancy event 3105 can include an event that is received fromone or more sources (e.g., event sources 3005, 3010 and/or 3015). Forexample, the enrichment manager 138 can receive an occupancy event. Theenrichment manager 138 can produce the enriched occupancy event 3105 byincluding the occupancy event and the additional information thatpertains to the occupancy event. For example, the additional informationcan be a location that the occupancy prediction pertains to (e.g., alocation within a building). Furthermore, the additional information caninclude one or more devices that are associated with the event (e.g.,badge scanners, Motion sensors, cameras). In some embodiments, theenrichment manager 138 can provide the enriched occupancy event to theoccupancy model 3110.

The occupancy model 3110 can use the enriched occupancy event 3105 togenerate an enriched occupancy prediction 3115. For example, theoccupancy model 3110 can produce occupancy predictions. The predictionscan include a predicted occupancy level. The predicted occupancy levelcan be for a building, a zone within a building, a floor within abuilding or any additional subset of the building. In some embodiments,the occupancy model 3110 can enrich the occupancy predictions by usingthe enriched occupancy event 3105. The occupancy model 3110 can enrichthe occupancy predictions by considering the information that isincluded with the enriched occupancy event 3105. The occupancy model3110 can determine that the enriched occupancy event 3105 providesinformation that shows that a previous occupancy prediction can beadjusted. For example, a previous predication can be that the occupancyfor a room is ten people. The occupancy model 3110 can use the enrichedoccupancy prediction 3115 to determine that the occupancy is higher orlower than then original prediction. As such, the occupancy model 3110can generate an enriched occupancy prediction 3115 by using the enrichedoccupancy event 3105. In some embodiments, the enriched occupancyprediction 3115 is generated when the occupancy model 3110 includes theenriched occupancy event 3105 with the occupancy predictions.

In some embodiments, the occupancy model 3110 can provide the enrichedoccupancy prediction 3115 to a digital twin manager 3120. The digitaltwin manager 3120 can use the enriched occupancy prediction 3115 todetermine one or more inferences. An inference can be the digital twinmanager 3120 associating the enriched occupancy prediction 3115 with oneor more addition models than can use the enriched occupancy prediction3115 to enrich one or more additional predictions. For example, thedigital twin manager can determine that the enriched occupancyprediction 3115 can impact an energy prediction and/or an equipmentprediction. The energy predication can relate to a predicted energymetric (e.g., energy consumption). The predicted energy metric can befor a building, a zone within a building, a floor within a building orany additional subset of the building. The equipment prediction canrelate to a predicted equipment action. For example, the equipmentprediction can be that the filtration of a building will be adjusted.

In some embodiments, the energy model 3125 can receive the enrichedoccupancy prediction 3115. The energy model 3125 can use the enrichedoccupancy prediction 3115 to enrich an energy prediction. For example,an enriched energy prediction 3140 can be generated by the energy model3125 by including the enriched occupancy prediction 3115 with the energypredictions. The energy model 3125 can determine that the enrichedoccupancy event 3105 provides information that shows that a previousenergy prediction can be adjusted. For example, a previous predictioncan be that the energy consumption for a building will have a certainmetric. The energy model 3125 can determine that the enriched occupancyprediction 3115 can impact the energy prediction. As such, the energymodel 3125 can generate the enriched energy prediction 3140 by using theenriched occupancy event 3105. In some embodiments, the energy model3125 can provide the enriched energy prediction 3140 to the enrichmentmanager 138.

In some embodiments, the equipment model 3130 can receive the enrichedoccupancy prediction 3115. The equipment model 3130 can use the enrichedoccupancy prediction 3115 to enrich an equipment prediction. Forexample, an enriched equipment prediction 3135 can be generated by theequipment model 3130 by including the enriched occupancy prediction 3115with the equipment predictions. The equipment model 3130 can determinethat the enriched occupancy event 3105 provides information that showsthat a previous equipment prediction can be adjusted. For example, aprevious prediction can be that an HVAC device will adjust thefiltration of a room. The equipment model 3130 can determine that theenriched occupancy prediction 3115 can impact the equipment prediction.As such, the equipment model 3130 can generate the enriched equipmentprediction 3135. In some embodiments, the equipment model 3130 canprovide the enriched equipment prediction 3135 to the enrichment manager138. In some embodiments, the occupancy model 3110 and/or the energymodel 3125 can use the enriched equipment prediction 3135 to generatethe enriched occupancy prediction 3115 and/or the enriched energyprediction 3140. In some embodiments, the occupancy model 3110 and/orthe equipment model 3130 can use the enriched energy prediction 3140 togenerate the enriched occupancy prediction 3115 and/or the enrichedequipment prediction 3135. In some embodiments, the enrichment manager138 can use the enriched energy prediction 3140 and/or the enrichedequipment prediction 3135 to generate the enriched occupancy event 3105.In some embodiments, the enrichment manager 138 can generate theenriched occupancy event 3105 by combining an occupancy event with theenriched energy prediction 3140 and/or the enriched equipment prediction3135. In some embodiments, the enriched occupancy prediction 3115 can beprovided to the enrichment manager 138. The enrichment manager 138 canthen further enrich the enriched occupancy event 3105 by combining theenriched occupancy event 3105 and the enriched occupancy prediction3115.

In some embodiments, the digital twin manager 3120 can execute, using anenriched event, a machine learning model. In some embodiments, theenriched event can be enriched events 3035, 3040, 3045 and/or enrichedoccupancy event 3105. In some embodiments, the machine learning modelcan be the occupancy model 3110, the energy model 3125 and/or theequipment model 3130.

In some embodiments, the digital twin manager 3120 can generate aninference of a characteristic of a building. For example, the inferencecan be that occupancy impacts energy consumption. In some embodiments,the digital twin manager 3120 can identify a second model that canexecute prediction using the inference. For example, the digital twinmanager 3120 can identify the energy model 3125. In some embodiments,the digital twin manager 3120 can provide the inference to the energymodel 3125.

In some embodiments, the digital twin manager 3120 can identifycontextual data that pertains to an inference. The digital twin manager3120 can enrich the inference by combining the inference and thecontextual data that pertains to the interference. In some embodiments,the digital twin manager 3120 can provide the enriched inference to oneor more machine learning models.

In some embodiments, the digital twin manager 3120 can generate aninference subscription that will route the inference to the machinelearning models that the digital twin manager 3120 has identifiedherein. In some embodiments, the digital twin manager 3120 can providethe inference to one or more machine learning models upon generating thesubscription.

Referring now to FIG. 32, an impact graph 3200 of a building is shown,according to an exemplary embodiment. The impact graph 3200 can includea zone node 3205, a floor node 3210 and/or a window node 3215. The floornode 3210 and the zone node 3205 have a relationship indicated by a hasAedge 3255. The hasA edge 3255 indicates that a floor has a zone. Thezone node 3205 and the window node 3215 have a relationship indicated bya hasA edge 3260. The hasA edge 3260 indicates that a zone has a window.The window node 3215 has a relationship with a window state node 3220.The relationship is indicated by a hasA edge 3285. The window state node3220 can indicate whether the window is open or closed. The window node3215 has a relationship with a window location node 3225. Therelationship is indicated by a hasA edge 3290. The window location node3225 can indicate a location of a window. The window node 3215 has arelationship with a window number node 3230. The relationship isindicated by a hasA edge 3295. The window number node 3230 can indicatea window identifier (e.g., a window number). The window metric can beused to differentiate one or more windows.

In some embodiments, the window node 3215 can have a relationship with autilities node 3235. The relationship is indicated by an impacts edge3280. The impacts edge 3280 can indicate that a window impactsutilities. The window node 3215 can have a relationship with an airquality node 3240. The relationship is indicated by an impacts edge3275. The impacts edge 3275 can indicate that a window impacts airquality. The window node 3215 can have a relationship with a temperaturenode 3245. The relationship is indicated by an impacts edge 3270. Theimpacts edge 3270 can indicate that a window impact temperature. Thewindow node 3215 can have a relationship with a device node 3250. Therelationship is indicated by an impacts edge 3265. The impacts edge 3265can indicate that a window impacts a device.

In some embodiments, the window state node 3220 can have one or moreimpacts. For example, if the temperature outside of a building is warmerthan the temperature inside the building and a window is opened thetemperature of the zone and/or the floor can be increased. Additionally,the air quality of the zone and/or the floor associated with the windowcan be adjusted. For example, if the pollen level is high outside of thebuilding the air quality within the building may decrease. The decreasein air quality and/or the increase in indoor temperature can impact adevice. The increase in the temperature can result in an HVAC devicetaking action to adjust the temperature. For example, the HVAC deviceincreases the ventilation rate of cold air. Similarly, the decrease inair quality can result in an HVAC device taking action to adjust the airquality. For example, the HVAC devices increase filtration in order toremove the pollen. The actions taken by the HVAC device can result inadditional energy consumption. The additional energy consumption canresult in increased utilities.

Referring now to FIG. 33, a process 3300 of enriching one or more eventsis shown, according to an exemplary embodiment. At least one-step of theprocess 3300 can be performed by the system 3000 described herein. Insome embodiments, the twin manager 108 and/or the cloud platform 106 canperform at least one step of the process 3300. Furthermore, anycomputing device described herein can perform at least one step of theprocess 3300.

In step 3305, the enrichment manager 138 can receive an event from anevent source. In some embodiments, the event source can be a buildingdata source of a building or an external data source. In someembodiments, the event source can be event sources 3005, 3010 and/or3015. In some embodiments, the event can be events 3020, 3025 and/or3030. The event received by the enrichment manager 138 can include dataand a timestamp. The data can include information about the event. Forexample, the information can be that the filtration rate of an HVACdevice was adjusted.

In step 3310, the enrichment manager 138 identifies contextual data thatcan describe the event in a digital twin. In some embodiments, theenrichment manager 138 can identify the contextual data by querying abuilding graph. For example, the enrichment manager 138 can identifycontextual data by querying the building graphs depicted in FIGS. 11-13and/or 32. For example, the enrichment manager 138 can identify one ormore nodes depicted in the building graph. Similarly, the enrichmentmanager 138 can identify one or more edges that pertain to the nodes.The contextual data can be additional information that is associatedwith the event received at step 3305. For example, the contextual datacan include at least one of a location where the event source islocated, one or more pieces of building equipment, one or morecapabilities associated with the pieces of building equipment and/or oneor more metrics associated with the pieces of building equipment. Insome embodiments, the contextual data can be any additional informationdescribed herein. In some embodiments, the contextual data can be thedata associated with events 3020, 3025 and/or 3030.

In step 3315, the enrichment manager 138 can enrich the event receivedat step 3305 by combining the contextual data identified at step 3310.In some embodiments, the enriched events can be enriched events 3035,3040 and/or 3045. In some embodiments, when the event received at step3305 and the contextual data that pertains to the event are combined anenriched event can be generated. For example, when event 3020 and thecontextual data that pertains to event 3020 are combined the enrichedevent 3035 can be generated.

In step 3320, the enrichment manager 138 can provide the enriched eventto a consuming system. For example, the enriched events provided by theenrichment manager 138 can be the enriched events 3035, 3040 and/or3045. In some embodiments, the consuming system can be the consumingsystem 3065 and/or the AI models 3070. The consuming system can generatean output upon receiving the enriched event. In some embodiments, thegenerated output can be the consuming system events 3080 and/or the AIdecisions 3075. In some embodiments, the enrichment manager 138 canreceive the output generated by the consuming system.

In step 3325, the enrichment manager 138 can identify contextual datathat is associated with the output event generated at step 3320. In someembodiments, the enrichment manager 138 can identify the contextual databy querying a building graph. For example, the enrichment manager 138can identify the contextual data by querying the building graphsdepicted in FIGS. 11-13 and/or 32. For example, the enrichment manager138 can identify one or more nodes depicted in the building graph.Similarly, the enrichment manager 138 can identify one or more edgesthat pertain to the nodes. In some embodiments, the contextual data canbe the additional information that was associated with the consumingsystem events 3080 and/or the AI decisions 3075.

In step 3330, the enrichment manager 138 can enrich the output event bycombining the output event and the contextual data identified at step3325. For example, the enriched output event can be the enrichedoccupancy event 3105. In some embodiments, the enrichment manager 138the generate output event can be the enriched events 3035, 3040 and/or3045. In some embodiments, the enriched output event can be generated bycombining the consuming system event 3080 and the contextual data thatpertains to the consuming system event 3080.

In step 3335, the enrichment manager 138 can provide the enriched outputevent to one or more consuming systems. In some embodiments, theenriched output event can be provided to the consuming system 3065, theAI model 3070, the occupancy model 3110, the energy model 3125, theequipment model 3130 and/or the digital twin manager 3120. In someembodiments, the providing of the enriched output event can be referredto as an enrichment loop.

Referring now to FIG. 34, a process 3400 of generating one or moresubscriptions is shown, according to an exemplary embodiment. Theprocess 3400 can be performed by the system 3000 described herein. Insome embodiments, the twin manager 108 and/or the cloud platform 106 canperform the process 3400.

In step 3405, the enrichment manager 138 can generate one or moresubscriptions. The enrichment manager 138 can generate the subscriptionsresponsive to receiving a request from a consuming system. The requestcan include one or more events and/or types of events that the consumingsystem would like to receive. For example, the request can include thatthe consuming system would like to receive temperature events.Furthermore, the request can include that the temperature events be froma certain location. For example, building A, floor 2 and zone E. In someembodiments, the enrichment manager 138 upon receiving a request caninterface with a subscription database (e.g., subscription database3085). In some embodiments, upon interfacing with the subscriptiondatabase 3085 the enrichment manager 138 can determine that asubscription does not exists. For example, the enrichment manager 138can determine that the events included within the request are not linkedto a subscription. In some embodiments, the enrichment manager 138, upondetermining that a subscription does not exist, can generate asubscription that links the events included with the request to theconsuming system that provided the request.

In step 3410, the enrichment manager 138 can receive an event from anevent source. In some embodiments, the event sources can be eventsources 3005, 3010 and/or 3015. The event can be events 3020, 3025and/or 3030. In some embodiments, the enrichment manager 138 caninterface with the subscription database 3085. The enrichment manager138 can identify one or more subscriptions and one or more consumingsystems that pertain to the event. For example, the enrichment manager138 can determine that event 3025 is linked to subscription 3050 andthat consuming system 3065 is enrolled in subscription 3050.

In step 3415, the enrichment manager 138 can identify contextual data.In some embodiments, the contextual data can be the additionalinformation that is associated with events 3020, 3025 and/or 3030. Insome embodiments, the enrichment manager 138 can identify the contextualdata by querying a building graph. For example, the building graphsdepicted in FIGS. 11-13 and/or 32. For example, the enrichment manager138 can identify one or more nodes depicted in the building graph.Similarly, the enrichment manager 138 can identify one or more edgesthat pertain to the nodes. In some embodiments, the enrichment manager138 can identify contextual data that pertains to the subscriptions thatare linked to the events. For example, contextual data that pertains tosubscription 3050.

In step 3420, the enrichment manager 138 can enrich the event receivedat step 3410. In some embodiments, the enrich events can be enrichedevents 3035, 3040 and/or 3045. In embodiments, the enrichment manager138 can enrich the event by combining the event receive at 3410 with thecontextual data that was identified at step 3415.

In step 3425, the enrichment manager 138 can provide the enriched eventto a consuming system. In some embodiments, the enrichment manager 138can provide enriched events to the consuming system that were identifiedat step 3410. In some embodiments, the enrichment manager 138 caninterface with the subscription database 3085 and identify one or moresubscriptions and/or one or more consuming devices that pertain to theenriched event. For example, the enrichment manager 138 can identifythat enriched event 3045 pertains to subscription 3060 and that the AImodel 3070 is enrolled in subscription 3060. In some embodiments, theenrichment manager 138, upon identifying subscription 3060 and the AImodel 3070, can provide the enriched event 3045 to the AI model 3070.

As an example, a subscription can be set up to provide temperatureevents for a particular building, Building A, and a particular floor,e.g., Floor Two. Because the events that are received and enriched canbe enriched with location information, e.g., Building A and Floor Two,the events can be provided, via the subscription or channel for thesubscription, to any system subscribed to the subscription. This canprovide flexibility since the consuming systems may not need tosubscribe to underlying pieces of equipment directly, e.g., to aparticular controller located in Building A on Floor Two or a particularthermostat located in Building A on Floor Two. The consuming system cansubscribe to a more generic channel, e.g., a channel that includes allevents. Because the contextual information is added to the events, theevents can be published to certain subscriptions based on the contextualinformation of the events. For example, temperature events that havebeen enriched with both an indication of Building A and Floor Two can bepublished to the subscription for temperature events for Building A andFloor Two. Furthermore, the underlying sources can be a mix of differenttypes of equipment, e.g., thermostats, sensors, controllers.Furthermore, the equipment can be replaced or new equipment can beadded. Because the consuming systems are subscribed to a subscriptionwith generic rules that are applied to the contextual informationenriched into the events, e.g., temperature events in Building A andFloor Two, the consuming system can receive, via the contextualinformation added into the events, all temperature events in Building Aand Floor Two regardless of the underlying equipment types, whetherequipment is replaced or adjusted, or whether new equipment is added toBuilding A and Floor 2.

In some embodiments, the enrichment manager 138 can receive an event(e.g., the event received in step 3305 and/or step 3410). The enrichmentmanger 138, responsive to receiving the event, can identify contextualdata that pertains to the event. The enrichment manager 138 can generatean enriched event (e.g., the enriched event generated in step 3315and/or step 3420). In some embodiments, the enrichment manager 138 canprovide the enriched event to a consuming system (e.g., the consumingsystem in step 3320 and/or in step 3425). The enrichment manager 138 canprovide the enriched event based on the consuming system being enrolledin a subscription. The consuming system, responsive to receiving theenriched event, can generate a consuming system event (e.g., the outputevent provided in step 3320). The consuming system event can be providedto the enrichment manager 138.

In some embodiments, the enrichment manager 138 can use the consumingsystem event to generate an enriched event (e.g., the enriched eventgenerated in step 3330). In some embodiments, the enrichment manager 138can provide the enriched event to the consuming system (e.g., theconsuming system in step 3320) that produced the consuming system eventand/or one or more additional consuming systems. In the embodiments, theadditional consuming systems can generate, responsive to receiving theenriched event, one or more additional consuming system events. In someembodiments, the additional consuming system events can be provided tothe enrichment manager 138. In some embodiments, the enrichment manager138 can provide the enriched event to a machine learning model (e.g.,the AI model 3070). The machine learning model, responsive to receivingthe enriched event, can generate an event (e.g., AI decision 3075). Insome embodiments, the event generated by the machine learning model canbe an inference. The event generated by the machine learning model canbe provided to the enrichment manager 138.

In some embodiments, the additional consuming system events can be atleast one of an alert, a change in a setpoint or any action otherwisedescribed herein. For example, an additional consuming system event canbe that the temperature setpoint for a zone should be changed. Theadditional consuming system event can include the new temperaturesetpoint. The additional consuming system event can be based on one ormore enriched events (e.g., the enriched events in step 3315, 3420and/or in step 3330. For example, the enriched event can include atemperature of a zone and the additional consuming system can use theenriched event to determine that the temperature of the zone can beadjusted.

In some embodiments, the enrichment manager 138 can provide an enrichedevent (e.g. the enriched event in step 3315 and/or in step 3420) to amachine learning model (e.g., the AI model 3070 in step 3320). Themachine learning model, responsive to receiving the enriched event, canproduce an event (e.g., the AI decision 3075). In some embodiments, theevent produced by the machine learning model can be an inference. Insome embodiments, the event produced by the machine learning model canbe provided to the enrichment manager 138.

In some embodiments, the enrichment manager 138 can produce an enrichedevent (e.g., the enriched event generated in step 3330) using the eventproduced by the machine learning model. In some embodiments, theenrichment manager 138 can provide the enriched event to one or moreadditional consuming systems (e.g., the consuming system 3065). In someembodiments, the additional consuming systems that receive the enrichedevent can produce, using the enriched event, one or more events (e.g.,consuming system events 3080). In some embodiments, the events producedby the additional consuming systems can be provided to the enrichmentmanager 138. In some embodiments, the enrichment manager 138 can providethe enriched event to one or more additional machine learning models. Insome embodiments, the additional machine learning models that receivethe enriched event can produce, using the enriched event, one or moreevents (e.g., the AI decisions 3075). In some embodiments, the eventsproduced by the additional machine learning models can be provided tothe enrichment manager 138.

The construction and arrangement of the systems and methods as shown inthe various exemplary embodiments are illustrative only. Although only afew embodiments have been described in detail in this disclosure, manymodifications are possible (e.g., variations in sizes, dimensions,structures, shapes and proportions of the various elements, values ofparameters, mounting arrangements, use of materials, colors,orientations, etc.). For example, the position of elements may bereversed or otherwise varied and the nature or number of discreteelements or positions may be altered or varied. Accordingly, all suchmodifications are intended to be included within the scope of thepresent disclosure. The order or sequence of any process or method stepsmay be varied or re-sequenced according to alternative embodiments.Other substitutions, modifications, changes, and omissions may be madein the design, operating conditions and arrangement of the exemplaryembodiments without departing from the scope of the present disclosure.

The present disclosure contemplates methods, systems and programproducts on any machine-readable media for accomplishing variousoperations. The embodiments of the present disclosure may be implementedusing existing computer processors, or by a special purpose computerprocessor for an appropriate system, incorporated for this or anotherpurpose, or by a hardwired system. Embodiments within the scope of thepresent disclosure include program products comprising machine-readablemedia for carrying or having machine-executable instructions or datastructures stored thereon. Such machine-readable media can be anyavailable media that can be accessed by a general purpose or specialpurpose computer or other machine with a processor. By way of example,such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROMor other optical disk storage, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to carry or storedesired program code in the form of machine-executable instructions ordata structures and which can be accessed by a general purpose orspecial purpose computer or other machine with a processor. Wheninformation is transferred or provided over a network or anothercommunications connection (either hardwired, wireless, or a combinationof hardwired or wireless) to a machine, the machine properly views theconnection as a machine-readable medium. Thus, any such connection isproperly termed a machine-readable medium. Combinations of the above arealso included within the scope of machine-readable media.Machine-executable instructions include, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing machines to perform a certain function orgroup of functions.

Although the figures show a specific order of method steps, the order ofthe steps may differ from what is depicted. Also two or more steps maybe performed concurrently or with partial concurrence. Such variationwill depend on the software and hardware systems chosen and on designerchoice. All such variations are within the scope of the disclosure.Likewise, software implementations could be accomplished with standardprogramming techniques with rule based logic and other logic toaccomplish the various connection steps, processing steps, comparisonsteps and decision steps.

In various implementations, the steps and operations described hereinmay be performed on one processor or in a combination of two or moreprocessors. For example, in some implementations, the various operationscould be performed in a central server or set of central serversconfigured to receive data from one or more devices (e.g., edgecomputing devices/controllers) and perform the operations. In someimplementations, the operations may be performed by one or more localcontrollers or computing devices (e.g., edge devices), such ascontrollers dedicated to and/or located within a particular building orportion of a building. In some implementations, the operations may beperformed by a combination of one or more central or offsite computingdevices/servers and one or more local controllers/computing devices. Allsuch implementations are contemplated within the scope of the presentdisclosure. Further, unless otherwise indicated, when the presentdisclosure refers to one or more computer-readable storage media and/orone or more controllers, such computer-readable storage media and/or oneor more controllers may be implemented as one or more central servers,one or more local controllers or computing devices (e.g., edge devices),any combination thereof, or any other combination of storage mediaand/or controllers regardless of the location of such devices.

What is claimed:
 1. A building system comprising one or more memorydevices having instructions stored thereon, that, when executed by oneor more processors, cause the one or more processors to: receive anevent from an event source, the event comprising data and a timestamp;identify first contextual data describing the event in a digital twin,the digital twin comprising a virtual representation of a building;enrich the event with the first contextual data; provide the enrichedevent to a consuming system, the consuming system generating an outputevent based on the enriched event; identify second contextual datadescribing the output event in the digital twin; enrich the output eventwith the second contextual data; and provide the enriched output eventto the consuming system or another consuming system.
 2. The buildingsystem of claim 1, wherein the instructions cause the one or moreprocessors to: execute an enrichment pipeline, the enrichment pipelineidentifying the first contextual data, enriching the event with thefirst contextual data, and outputting the enriched event; and feed theoutput event back into an input of the enrichment pipeline, theenrichment pipeline identifying the second contextual data, enrichingthe output event with the second contextual data, and outputting theenriched output event.
 3. The building system of claim 1, wherein theconsuming system generates the output event based on the data of theenriched event and the first contextual data of the enriched event. 4.The building system of claim 1, wherein the instructions cause the oneor more processors to: execute one or more enrichment rules to identifythe contextual data from the digital twin, the digital twin comprising aplurality of types of contextual data for a plurality of event sources;and the one or more enrichment rules identifying types of contextualinformation for the event source.
 5. The building system of claim 1,wherein the instructions cause the one or more processors to: identifythe first contextual data by performing a first search of the digitaltwin; and identify the second contextual data by performing a secondsearch of the digital twin.
 6. The building system of claim 1, whereinthe digital twin includes a building graph; wherein the instructionscause the one or more processors to: identify the first contextual databy performing a first search of the building graph; and identify thesecond contextual data by performing a second search of the buildinggraph.
 7. The building system of claim 1, wherein the contextual dataincludes at least one of: a location within the building that the eventsource is located; an indication of one or more pieces of buildingequipment of the event source; or one or more capabilities associatedwith the pieces of building equipment.
 8. The building system of claim1, wherein the event source is at least one of: an internal data sourcelocated within the building; or an external data source located outsidethe building.
 9. The building system of claim 1, wherein the digitaltwin includes a building graph, the building graph comprising: aplurality of nodes representing a plurality of entities of the building,wherein at least a portion of the plurality of nodes represent the firstcontextual data, the second contextual data, the event source, and theconsuming system; and a plurality of edges between the plurality ofnodes, wherein the plurality of edges represent relationships betweenthe plurality of entities of the building.
 10. The building system ofclaim 9, wherein the instructions cause the one or more processors to:identify the first contextual data by: identifying a first node of theplurality of nodes representing the event source; and identifying afirst edge of the plurality of edges between the first node and a secondnode representing the first contextual data.
 11. The building system ofclaim 1, wherein the instructions cause the one or more processors to:execute a first machine learning model using the enriched event togenerate an inference of a characteristic of the building; identify asecond machine learning model that executes on the inference of thecharacteristic of the building; and communicate the inference of thecharacteristic to the second machine learning model.
 12. The buildingsystem of claim 11, wherein the instructions cause the one or moreprocessors to: identify third contextual data of the digital twin forthe inference of the characteristic of the building; and enrich theinference with the third contextual data; and execute the second machinelearning model based on the inference enriched with the third contextualdata.
 13. The building system of claim 11, wherein the instructionscause the one or more processors to: generate a subscription that routesthe inference to the second machine learning model responsive toidentifying that the second machine learning model executes on theinference of the characteristic of the building; and provide theinference, based on the subscription, to the second machine learningmodel.
 14. A method comprising: receiving, by a processing circuit, froman event source, an event, the event comprises data and a timestamp;identifying, by the processing circuit, first contextual data describingthe event in a digital twin, the digital twin comprising a virtualrepresentation of a building; enriching, by the processing circuit, theevent with the first contextual data; providing, by the processingcircuit, to a consuming system, the enriched event, the consuming systemgenerating an output event based on the enriched event; identifying, bythe processing circuit, second contextual data describing the outputevent in the digital twin; enriching, by the processing circuit, theoutput event with the second contextual data; and providing, by theprocessing circuit, to the consuming system or another consuming system,the enriched output event.
 15. The method of claim 14, furthercomprising: executing, by the processing circuit, an enrichmentpipeline, the enrichment pipeline identifying the first contextual data,enriching the event with the first contextual data, and outputting theenriched event; and feeding, by the processing circuit, the output eventback into an input of the enrichment pipeline, the enrichment pipelineidentifying the second contextual data, enriching the output event withthe second contextual data, and outputting the enriched output event.16. The method of claim 14, further comprising: executing, by theprocessing circuit, a first machine learning model using the enrichedevent to generate an inference of a characteristic of the building;identifying, by the processing circuit, a second machine learning modelthat executes on the inference of the characteristic of the building;and communicating, by the processing circuit, the inference of thecharacteristic to the second machine learning model.
 17. The method ofclaim 14, further comprising: identifying, by the processing circuit,third contextual data of the digital twin for the inference of thecharacteristic of the building; and enriching, by the processingcircuit, the inference with the third contextual data; and executing, bythe processing circuit, the second machine learning model based on theinference enriched with the third contextual data.
 18. The method ofclaim 14, further comprising: executing, by the processing circuit, oneor more enrichment rules to identify the contextual data from thedigital twin, the digital twin comprising a plurality of types ofcontextual data for a plurality of event sources; and the one or moreenrichment rules identifying types of contextual information for theevent source.
 19. The method of claim 14, wherein the digital twinincludes a building graph, the building graph comprising: a plurality ofnodes representing a plurality of entities of the building, wherein atleast a portion of the plurality of nodes represent the first contextualdata, the second contextual data, the event source, and the consumingsystem; and a plurality of edges between the plurality of nodes, whereinthe plurality of edges represent relationships between the plurality ofentities of the building.
 20. A building system comprising: one or morememory devices having instructions thereon; and one or more processorsconfigured to execute the instructions causing the one or moreprocessors to: receive an event from an event source, the eventcomprising data and a timestamp; identify first contextual datadescribing the event in a digital twin, the digital twin comprising avirtual representation of a building; enrich the event with the firstcontextual data; provide the enriched event to a consuming system, theconsuming system generating an output event based on the enriched event;identify second contextual data describing the output event in thedigital twin; enrich the output event with the second contextual data;and provide the enriched output event to the consuming system or anotherconsuming system.